Patent Publication Number: US-9848458-B2

Title: Wireless parameter-sensing node and network thereof

Description:
FIELD OF THE DISCLOSURE 
     Embodiments of the present invention relate to a wireless parameter-sensing node in a network thereof, and more particularly to a parameter-sensing node such as mobile telephone in a mobile-telephony network. 
     BACKGROUND 
     In a wireless communication network, nodes are connected wirelessly to the network. In some wireless networks, the wirelessly-connected nodes are themselves physically mobile, e.g., a conventional mobile-telephony network. While user equipment (UE), e.g., mobile telephones, attached to a conventional mobile-telephony network are themselves physically mobile, their communication is supported by physically stationary infrastructure, namely stationary base stations in different locations that communicate with a remote, stationary mobile-telephone-switching office (MTSO). A given one of the UEs can move from the coverage area of a first base station into the coverage area of a second base station. To facilitate the handoff of a given UE from the first base station to the second base station, some received signal strength data are collected by and received from the given UE by the first base station. 
     Many locations throughout the world lack such physically-stationary network infrastructures and/or exist under conditions that deter, if not prevent, construction of the same. In a war zone, for example, building stationary network infrastructure is not feasible due, e.g., to the transient nature of military personnel and equipment. 
     One device that can be used to improve communications in such environments is a mobile cellular network (MCN) communication system. Aside from the UEs, in an MCN, all of the components of a typical cellular network reside in one device (referred to herein as a network-in-a-box (NIB)). The NIB itself is mobile. The MCN provides an example of a wireless network in which not only the wirelessly-connected nodes themselves are physically mobile, but the infrastructure that supports their communication (namely, the NIB) also is physically mobile. 
     The NIB is self-contained in that it does not need to communicate with other base stations or an MTSO to provide complete cellular network functionality to instances of user equipment (UEs) within its area of coverage. One example of a commercially available NIB is the XIPHOS™ available from OCEUS NETWORKS™. 
     As an NIB moves, the network coverage (that it provides) moves with it. To increase the range of a MCN, multiple NIBs can be networked together to create a network of MCN communication systems, also referred to herein as a NOM. Among other things, the MCN communication system can perform handover operations when a UE moves from one coverage area to another coverage area within the NOM. Furthermore, if an MCN communication system moves from one location to another, the NOM can allocate affected UEs between the moving MCN communication system and other MCN communication systems in the area. 
     SUMMARY 
     It is to be understood that both the following summary and the detailed description are exemplary and explanatory and are intended to provide further explanation of the present invention as claimed. Neither the summary nor the description that follows is intended to define or limit the scope of the present invention to the particular features mentioned in the summary or in the description. Rather, the scope of the present invention is defined by the appended claims. 
     In certain embodiments, the disclosed embodiments may include one or more of the features described herein. 
     An aspect of the present invention provides a wireless parameter-sensing node in a network thereof, the parameter-sensing node comprising: sensors to sample values of parameters, respectively; a memory; a collection engine configured to: selectively collect data representing at least some of the sampled values, respectively; and store the collected data in the memory; an omega engine configured to: retrieve selected portions of the collected data from the memory; and send the selected portions to a remote host; wherein at least one of the collection, the storage, the retrieval and the sending are performable according to one or more reconfigurable collection-control criteria, one or more reconfigurable storage-control criteria, one or more reconfigurable retrieval-control criteria and one or more reconfigurable reporting-control criteria, respectively, stored in the memory. 
     Another aspect of the present invention provides a client-server computer architecture comprising: a first host; and a taskor server executable on the first host and configured to: receive a query from a taskee client for an unspecified one amongst a plurality of tasks; make a selection of a given one from amongst the plurality of tasks; indicate the selected task to the taskee client; and receive a report including execution results for the selected task from the taskee client. 
     A further aspect of the present invention is to provide a client-server computer architecture comprising: a first host; and a taskee client executable on the first host and configured to: query a taskor server for an unspecified one amongst a plurality of tasks, a consequent selection of a given one from amongst the plurality tasks being performable by the taskor server; receive an indication of the given task from the taskor server; facilitate execution of the given task on the first host; and report execution-results of the given task to the taskor server. 
     Yet another aspect of the present invention is to provide method of operating at least one wireless parameter-sensing node in a network thereof, the at least one node including sensors to sample values of parameters, respectively, and a memory, the method comprising: selectively collecting data representing at least some of the sampled values, respectively; and storing the collected data in the memory; retrieving selected portions of the collected data from the memory; and sending the selected portions to a remote host; wherein at least one of the collection, the storage, the retrieval and the sending are performable according to one or more reconfigurable collection-control criteria, one or more reconfigurable storage-control criteria, one or more reconfigurable retrieval-control criteria and one or more reconfigurable reporting-control criteria, respectively, stored in the memory. 
     These and further and other objects and features of the present invention are apparent in the disclosure, which includes the above and ongoing written specification, with the drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The accompanying drawings, which are incorporated herein and form a part of the specification, illustrate exemplary embodiments and, together with the description, further serve to enable a person skilled in the pertinent art to make and use these embodiments and others that will be apparent to those skilled in the art. Embodiments of the present invention will be more particularly described in conjunction with the following drawings wherein: 
         FIG. 1A  is a block diagram of a network of wireless parameter-sensing nodes, according to an embodiment of the present invention; 
         FIG. 1B  is a more detailed block diagram of one of the UEs and the NIB of  FIG. 1A , according to an embodiment of the present invention; 
         FIG. 1C  is a block diagram illustrating examples of criteria that can be stored in the settings repository, according to an embodiment of the present invention; 
         FIG. 1D  is a communication-layer diagram illustrating the path of flow during a communication session between the omega engine of the UE and the alpha engine of the NIB, according to an embodiment of the present invention; 
         FIG. 2A  is an example of a state diagram for the collection engine of the UE, according to an embodiment of the present invention; 
         FIGS. 2B and 2C  are examples of state diagrams for the omega engine of the UE, according to embodiments of the present invention, respectively; 
         FIG. 3A  is a database-schema diagram illustrating an example of possible relationships amongst data collected and then organized into sets thereof by the collection engine of the UE, according to an embodiment of the present invention; 
         FIGS. 3B and 3C  are a flowchart and a corresponding database-schema diagram illustrating an aspect of the operation of the collection engine of the UE, according to an embodiment of the present invention; 
         FIGS. 3D and 3E  are a flowchart and a message-assembly diagram illustrating an aspect of the operation of the omega engine of the UE, according to an embodiment of the present invention; 
         FIGS. 3F and 3G  are a flowchart and a database-schema diagram illustrating an aspect of the operation of the collection engine of the UE, according to an embodiment of the present invention; 
         FIGS. 3H, 3I and 3J  are a database-schema diagram, a flowchart and a database-schema diagram, respectively, illustrating an aspect of the operation of the collection engine, according to an embodiment of the present invention; 
         FIG. 4  is a flow diagram of interactions that can occur in a taskee-client—taskor-server relationship, according to an embodiment of the present invention; 
         FIG. 5  is an example of a UML (uniform modeling language) sequence diagram, according to an embodiment of the present invention, that is a counterpart to the flowchart of  FIG. 4 ; 
         FIG. 6  is an example of a state diagram for a taskee-client (omega engine), according to an embodiment of the present invention; and 
         FIG. 7  is a block diagram of two instances of node and an alternative remote host, according to an embodiment of the present invention. 
     
    
    
     DETAILED DESCRIPTION 
     Embodiments of wireless parameter-sensing node in a network thereof will now be disclosed in terms of various exemplary embodiments. This specification discloses one or more embodiments that incorporate features of the present invention. The embodiment(s) described, and references in the specification to “one embodiment”, “an embodiment”, “an example embodiment”, etc., indicate that the embodiment(s) described may include a particular feature, structure, or characteristic. Such phrases are not necessarily referring to the same embodiment. The skilled artisan will appreciate that a particular feature, structure, or characteristic described in connection with one embodiment is not necessarily limited to that embodiment but typically has relevance and applicability to one or more other embodiments. 
     In the several figures, like reference numerals may be used for like elements having like functions even in different drawings. The embodiments described, and their detailed construction and elements, are merely provided to assist in a comprehensive understanding of the present invention. Thus, it is apparent that the present invention can be carried out in a variety of ways, and does not require any of the specific features described herein. Also, well-known functions or constructions are not described in detail since they would obscure the present invention with unnecessary detail. 
     The description is not to be taken in a limiting sense, but is made merely for the purpose of illustrating the general principles of the present invention, since the scope of the present invention is best defined by the appended claims. 
     It should also be noted that in some alternative implementations, the blocks in a flowchart, the communications in a sequence-diagram, the states in a state-diagram, etc., may occur out of the orders illustrated in the figures. That is, the illustrated orders of the blocks/communications/states are not intended to be limiting. Rather, the illustrated blocks/communications/states may be reordered into any suitable order, and some of the blocks/communications/states could occur simultaneously. 
     All definitions, as defined and used herein, should be understood to control over dictionary definitions, definitions in documents incorporated by reference, and/or ordinary meanings of the defined terms. 
     The indefinite articles “a” and “an,” as used herein in the specification and in the claims, unless clearly indicated to the contrary, should be understood to mean “at least one.” 
     The phrase “and/or,” as used herein in the specification and in the claims, should be understood to mean “either or both” of the elements so conjoined, i.e., elements that are conjunctively present in some cases and disjunctively present in other cases. Multiple elements listed with “and/or” should be construed in the same fashion, i.e., “one or more” of the elements so conjoined. Other elements may optionally be present other than the elements specifically identified by the “and/or” clause, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, a reference to “A and/or B”, when used in conjunction with open-ended language such as “comprising” can refer, in one embodiment, to A only (optionally including elements other than B); in another embodiment, to B only (optionally including elements other than A); in yet another embodiment, to both A and B (optionally including other elements); etc. 
     As used herein in the specification and in the claims, “or” should be understood to have the same meaning as “and/or” as defined above. For example, when separating items in a list, “or” or “and/or” shall be interpreted as being inclusive, i.e., the inclusion of at least one, but also including more than one, of a number or list of elements, and, optionally, additional unlisted items. Only terms clearly indicated to the contrary, such as “only one of or “exactly one of,” or, when used in the claims, “consisting of,” will refer to the inclusion of exactly one element of a number or list of elements. In general, the term “or” as used herein shall only be interpreted as indicating exclusive alternatives (i.e. “one or the other but not both”) when preceded by terms of exclusivity, such as “either,” “one of,” “only one of,” or “exactly one of” “Consisting essentially of,” when used in the claims, shall have its ordinary meaning as used in the field of patent law. 
     As used herein in the specification and in the claims, the phrase “at least one,” in reference to a list of one or more elements, should be understood to mean at least one element selected from any one or more of the elements in the list of elements, but not necessarily including at least one of each and every element specifically listed within the list of elements and not excluding any combinations of elements in the list of elements. This definition also allows that elements may optionally be present other than the elements specifically identified within the list of elements to which the phrase “at least one” refers, whether related or unrelated to those elements specifically identified. Thus, as a non-limiting example, “at least one of A and B” (or, equivalently, “at least one of A or B,” or, equivalently “at least one of A and/or B”) can refer, in one embodiment, to at least one, optionally including more than one, A, with no B present (and optionally including elements other than B); in another embodiment, to at least one, optionally including more than one, B, with no A present (and optionally including elements other than A); in yet another embodiment, to at least one, optionally including more than one, A, and at least one, optionally including more than one, B (and optionally including other elements); etc. 
     In the claims, as well as in the specification above, all transitional phrases such as “comprising,” “including,” “carrying,” “having,” “containing,” “involving,” “holding,” “composed of,” and the like are to be understood to be open-ended, i.e., to mean including but not limited to. Only the transitional phrases “consisting of” and “consisting essentially of” shall be closed or semi-closed transitional phrases, respectively, as set forth in the United States Patent Office Manual of Patent Examining Procedures, Section 2111.03. 
     It will be understood that, although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, without departing from the scope of example embodiments. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. 
     The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments. Additionally, all embodiments described herein should be considered exemplary unless otherwise stated. 
     The word “network” is used herein to mean one or more conventional or proprietary networks using an appropriate network data transmission protocol. Examples of such networks include, PSTN, LAN, WAN, WiFi, WiMax, Internet, 35 World Wide Web, Ethernet, other wireless networks, and the like. 
     The phrase “wireless device” is used herein to mean one or more conventional or proprietary devices using radio frequency transmission techniques. Examples of such wireless devices include cellular telephones, desktop computers, laptop computers, handheld computers, electronic games, portable digital assistants, MP3 players, DVD players, or the like. 
     In developing embodiments of the present invention, among other things, the inventors thereof:
         were mindful that reducing bandwidth consumption is an ongoing design consideration and managing bandwidth consumption is an ongoing management consideration in general for wireless communication networks, in particular for a conventional mobile-telephony network, and yet more particularly for a mobile cellular network (MCN) communication system;   recognized, in the context of a UE-handover in an MCN communication system, that it may be beneficial for a given UE to collect more signal strength data and provide the same to the NIB than is typically collected and received in preparation for a handover in the conventional mobile-telephony network by a base station;   recognized, not only in the circumstance of a UE-handover but in other circumstances in the context of an MCN communication system, that it may be beneficial for a given UE to collect data (and provide the same to the NIB) that is not collected by a conventional UE and/or that is collected by a conventional UE but not received by a base station in the conventional mobile-telephony network;   recognized that the desired amount of data that is collected by a given UE and/or that is retrieved by an NIB varies on a per-UE basis, i.e., varies between different instances of a UE (even under circumstances in which all of the UEs served by the NIB are instances of substantially the same combination of hardware and software);   recognized that the per-UE variation in the desired amount of data that is collected by a given UE and/or that is retrieved by an NIB varies according to multiple factors including (but not limited to):
           the location of the given UE relative to the NIB;   the motion of the given UE relative to the NIB;   the time of day (in general);   the mission-requirements of the user on which is borne the given UE (e.g., where the user is a warrior in the context of a war zone, a rescuer in the context of a disaster-response scenario, etc.);   the momentary phase of a multi-phase mission of the user on which is borne the given UE (e.g., where the user is a warrior in the context of a war zone, a rescuer in the context of a disaster-response scenario, etc.); and   the momentary level of danger being encountered by the user on which is borne the given UE (e.g., where the user is a warrior in the contexts of a war zone, a rescuer in the context of a disaster-response scenario, etc.);   
           recognized that the desired amount of data collection by an NIB relative to a given UE varies depending on the circumstances under which the NIB is operating, e.g., at a given moment, the NIB might be servicing other UEs which are facing more demanding circumstances than the given UE such that the priority-level attributed to collecting data by the other UEs and/or receiving collected data therefrom at that time is higher than the priority-level for the given UE; and   recognized that (1) a UE which has at least one of dynamically reconfigurable data collection capability, dynamically reconfigurable local data storage capability, dynamically reconfigurable local data retrieval capability and dynamically reconfigurable capability of sending collected data to host (e.g., an NIB) and (2) a host (e.g., an NIB) that can dynamically control such reconfigurations can advantageous, e.g., in terms of facilitating the management of bandwidth consumption in general for wireless communication networks, and in particular for an NIB.
 
One or more embodiments of the present invention provide an MCN communication system that includes such a dynamically reconfigurable UE and a corresponding NIB that can dynamically control such reconfiguration, and corresponding methods of operation.
       

       FIG. 1A  is a block diagram of a network  100  of wireless parameter-sensing nodes, according to an embodiment of the present invention. 
     In  FIG. 1A , network  100  includes multiple nodes  102  that communicate wirelessly, i.e., via wireless communication sessions  104 , respectively, with a remote host  106 . For example, network  100  can be a mobile-telephony network or a mobile cellular network (MCN) communication system such that host  106  is a base station or a network-in-a-box (NIB), respectively, and nodes  102  are instances of user equipment (UE) that can engage in radio telephony with NIB  106 . Among other things, NIB  106  includes a wireless interface, e.g., an LTE (Long Term Evolution) modem (not illustrated), a WiFi modem (not illustrated), etc., by which to communicate with nodes  102  via wireless communication sessions  104 , respectively. 
     An instance of node  102  can be any device that includes a wireless interface, e.g., an LTE modem (not illustrated), a WiFi modem (not illustrated), etc., by which to communicate with NIB  106  via a wireless communication session  104 . For example, node  102  can be a mobile phone (e.g., a smart mobile phone running the ANDROID™ operating system, a laptop/notebook computer, a tablet computer, a dedicated GPS (Global Positioning System) receiver, a smart sensor, etc.) Additionally, such LTE-modem-equipped devices further include computing components (not illustrated in  FIG. 1A ), e.g., one or more processor units, one or more communications buses, one or more memories, one or more interfaces (e.g., a man-machine interface), etc. Each UE  102  communicates with NIB  106  via a wireless communication session  104 , respectively. 
     Also included in  FIG. 1A  is an exploded of one of UEs  102  that illustrates some (but not all) of the operational components of UEs  102 . As such, each UE  102  includes: an omega engine  108 ; dynamically reconfigurable criteria  110  by which the operation of omega engine  108  is controlled; a memory  112  to store collected data locally; a sensor-data collection engine  114 ; and dynamically reconfigurable criteria  116  by which the operation of collection engine  114  is controlled. Criteria  110  and  116  can be stored in one or more of the noted (above) albeit not-illustrated (in FIG.  1 A) memories. Omega engine  108  and collection engine  114  can be implemented, for example, as executable code (e.g., an ANDROID™ background service) stored in one or more of the noted (above) albeit not-illustrated (in  FIG. 1A ) memories in UE  102  and executed by one or more of the noted (above) albeit not-illustrated (in  FIG. 1A ) processor units in UE  102 , respectively. For ease of illustration, communication session  104  is illustrated as terminating in omega engine  108 . 
     A detailed discussion of the components and operation of UEs  102  and NIB  106  appear below in the discussion of other FIGS. Briefly, however, it should be understood that UE  102  also includes operational components (not illustrated in  FIG. 1A ) and various sensors (not illustrated in  FIG. 1A ) which sense parameters (at least some of which are operational parameters of the operational components) and sample the same to thereby generate data representing the sampled values, respectively. According to instances of criteria  116 , collection engine  114  selectively collects data representing at least some of the sampled values, respectively, and stores the collected sensor data into memory  112 . According to instances of criteria  110 , omega engine  106  selectively retrieves portions of the collected data from memory  112  and periodically sends the selected portions to NIB  106  in messages  118  during wireless communication sessions  104 , respectively. 
     In other words, network  102  of  FIG. 1A  is an example of a mobile cellular network (MCN) communication system that includes: dynamically reconfigurable UEs  102 ; and a corresponding NIB  106  that can dynamically and selectively control the reconfiguration of UEs  102 . 
       FIG. 1B  is a more detailed block diagram of one of UEs  102  and NIB  106 , according to an embodiment of the present invention. 
     As briefly introduced above (in the discussion of  FIG. 1A ), UE  102  includes various sensors, which can be internal components of UE  102  and/or discrete external components coupled to UE  102 . At least some of the internal sensors can be configured to sense at least some of the operational parameters of the operational components of UE  102 . Some (but not all) of the various sensors are illustrated in  FIG. 1B . Examples of such sensors include: a position sensor  124 , e.g., based on a global positioning system (GPS) receiver (not illustrated in  FIG. 1B ; one or more platform sensors  126 ; one or more sensors  128  associated with and measuring operating parameters of a radio-telephony system (not illustrated in  FIG. 1B ), respectively; an orientation sensor  130 , e.g., based on a geomagnetic field sensor (not illustrated in  FIG. 1B ) and one or more accelerometers (not illustrated in  FIG. 1B ); and one or more sensors  132  associated with and measuring operating parameters of a power system (not illustrated in  FIG. 1B ), respectively. 
     Parameters from sensors  124 - 132  can be grouped into a set of domains. More particularly, parameters associated with sensors  124  and  130  can be included in a location domain. Examples of parameters in the location domain associated with sensor  124  include: a GPS-derived altitude; a GPS-derived latitude; a GPS-derived longitude; a GPS-derived time; a GPS-derived heading; etc. Examples of parameters in the location domain associated with sensor  132  include: a multi-dimensional array including geomagnetic field strength values for each coordinate axis in a standard three-axis coordinate system; a multi-dimensional array including azimuth (yaw), pitch, and roll values, etc. 
     Parameters associated with the one or more sensors  128  can be included in a telephony domain. Examples of parameters in the telephony domain associated with the one or more sensors  128  include: an Access Point Name (APN); a Channel Quality Indicator (CQI); an Internet Protocol (IP) address; a Public Land Mobile Network (PLMN) identifier; a Reference Signal Received Power (RSRR) indicator; a Reference Signal Received Quality (RSRQ) indicator; a Reference Signal Signal-To-Noise Ratio (RSSNR) indicator; etc. 
     Parameters associated with the one or more sensors  132  can be included in a power domain. Examples of parameters in the power domain associated with the one or more sensors  132  include: a health index of a battery on the mobile device; a charge level indicating a level of charge remaining in the battery; a plugged state indicator of whether a battery-charger is being charged by a charger; a battery presence indicator of whether a battery is present on the mobile device; a battery status indicator of whether the battery is charging or discharging; a battery temperature; a battery voltage; etc. 
     Parameters associated with the one or more sensors  126  can be included in a platform domain. Examples of parameters in the platform domain associated with the one or more sensors  126  include: a name of the UE  102 ; a serial number of UE  102 ; an elapsed uptime of UE  102 ; an amount of free memory on UE  102 ; a total amount of memory on UE  102 ; an International Mobile Station Equipment Identity (IMEI); an International Mobile Subscriber Identity (IMSI); an indicator of an operating system (OS) on UE  102 ; a version number of the OS on UE  102 ; etc. 
     In  FIG. 1B , UE  102  is illustrated as further including an image processor  134  and a camera  136 , e.g., a digital camera. A variety of devices (not illustrated) can be mounted to UE  102  by which a given sample of a fluid can be disposed in the optical field of camera  136  and, if needed, illuminated. Such devices are analogous to a stage of a microscope, wherein the stage is configured to receive a sample of fluid pressed between two slides and to dispose the same in the optical field of the microscope. When an image of the given fluid sample is processed by image processor  134  according to appropriate corresponding image-processing software executable thereon (not illustrated), together camera  136  and image processor  134  can function, e.g., as a lens-free digital microscope, which is another type sensor (and is denoted in  FIG. 1B  as sensor  137 ). Such a lens-free digital microscope can, for example, analyze: a blood sample to determine red and/or white blood cell counts and/or spot viruses (such as influenza, HIV, etc.); a urine sample to identify indications of dehydration, kidney disease, etc.; a water sample to identify the presence of parasites (e.g., bacteria, etc.), toxic chemicals (e.g., Mercury, etc.), etc. 
     As noted, UE  102  may include sensors that are discrete external components which are externally coupled to UE  102 . For example, UE  102  might be coupled to vital-sign sensors  140  that sense vital signs (e.g., heart rate, respiration rate, blood pressure, body temperature, etc.) of a user (e.g., a warrior, rescuer, etc.) associated with (and on which is borne) UE  102 . As a further example, UE  102  might be coupled to one or more sensors  138  that sense conditions to which are exposed UE  102  and the user (e.g., a warrior, rescuer, etc.) associated with (and on which is borne) UE  102 , e.g., ambient barometric pressure, ambient temperature, nuclear radiation, chemical agents, electric fields (RF (radio frequency), microwave, etc.), magnetic fields, etc. 
     The set of domains discussed above can also include domains corresponding to sensors  137 - 140 . More particularly, parameters associated with sensors  137  and  138  can be included in an environment domain. Examples of parameters in the environment domain associated with sensor  124  include: blood red and/or white blood cell counts (relative to a blood sample); flags representing the presence of various viruses, respectively (relative to a blood sample); parameters typically included in a urinalysis (relative to a urine sample); a flag representing the presence of any parasites (relative to a water sample); flags representing the presence of particular parasites (relative to a water sample); etc. Examples of parameters in the environment domain associated with sensor  138  include: ambient temperature; ambient barometric pressure; detected presence of nuclear radiation; cumulative exposure to nuclear radiation, detected presence of one or more chemical agents, detected present of electric fields (RF, microwave, etc.), detected presence of magnetic fields, etc. 
     Parameters associated with sensor  140  can be included in a user domain. Examples of parameters in the user domain associated with sensor  140  include: a user body temperature; a user pulse rate; a user respiration rate; a user blood oxygen level; a user electrocardiogram (EKG); a user blood cell count; etc. 
     In  FIG. 1B , UE  102  is illustrated as further including: a memory  122  that includes a settings repository. As briefly introduced above (in the discussion of  FIG. 1A ), according to instances of dynamically reconfigurable criteria  116  and  110 , collection engine  114  and omega engine  106  are configured to operate, respectively. Refreshed instances of criteria  110  and  116  (e.g., formatted as one or more XML files) can be included in messages  120 . Omega engine  108  is further configured to receive messages  120  during wireless communication sessions  104 , respectively, and to store the refreshed instances of reconfigurable criteria  110  and  116  (e.g., formatted as one or more XML files) in settings repository  122 . In other words, omega engine  108  is configured to update criteria  110  and  116  with the refreshed instances of criteria  110  and  116 . 
       FIG. 1C  is a block diagram illustrating examples of criteria that can be stored in settings repository  122 , according to an embodiment of the present invention. 
     In  FIG. 1C , settings repository  122  includes reconfigurable criteria  116  and reconfigurable criteria  110 , e.g., represented by one or more XML-formatted files. Criteria  116  can include, e.g., reconfigurable collection-control criteria  142  and reconfigurable storage-control criteria  144 . Criteria  110  can include, e.g., reconfigurable retrieval-control criteria  146  and reconfigurable reporting-control criteria  148 . 
     Reconfigurable collection-control criteria  142  can include, e.g., a frequencies-of-collection list  162 , alarm criteria  164  and a subject list  166 . Reconfigurable storage-control criteria  144  can include, e.g., an overwrite rule  168  and a depth chart  170 . Retrieval-control criteria  146  can include, e.g., a withdrawal rule  172 . Reporting-control criteria  148  can include, e.g., a frequency-of-initiation setting  174 , packaging criteria  176 , a recipient setting  178  and emergent criteria  180 . 
     Returning to the discussion of  FIG. 1B , as collection engine  114  is configured to operate according to criteria  116 , accordingly collection engine  114  is further configured to operate according to collection-control criteria  142  and storage-control criteria  144  (because they are included in criteria  116 ), which collection engine  114  can read from settings repository  122 . If collection engine  114  were to collect data from all of sensors  124 - 140 , the resulting set of data would be a full set of data. Typically, however, collection-control criteria  142  configures collection engine  114  to collect at least some but less than all of the data from sensors  124 - 140 , i.e., a non-empty, proper subset of the full set. 
     More particularly, subject list  166  (which is included in collection-control criteria  142 ) defines which ones amongst the various parameters sensed by sensors  124 - 140  will data representative thereof be collected by collection engine  114 . Frequencies-of-collection list  162  (which is included in collection-control criteria  142 ) defines collection frequencies at which data (representative of parameters sensed by sensors  124 - 140 ) is to be collected, respectively, by collection engine  114 . In other words, collection engine  114  is further configured to cull such data according to subject list  166  (controls which ones) and frequencies-of-collection list  162  (controls how often). 
     Subject list  166  can also organize selected ones of the parameters (sensed by sensors  124 - 140 ) into groups, respectively. Frequencies-of-collection list  162  indicates the collection frequencies at which data for the groups are to be collected, respectively. Accordingly, collection engine  114 , relative to a given one of the groups, is further configured to: cull such data for the selected parameters in the group (as defined by subject list  166 ) according to the corresponding collection frequency indicated in frequencies-of-collection list  162  so as to produce resulting sets of data for which the data included therein are sampled, e.g., at substantially the same times, respectively. 
     Memory  112  is of finite storage capacity. If not otherwise constrained, then (over the elapse of a sufficient amount of time) collection engine  114  would be able to accumulate more data, e.g., more instances of each set of data, than could fit in memory  112 . To deal with the problem of too much data for too little storage capacity, depth chart  170  and overwrite rule  168  are provided. 
     Depth chart  170  (which is included in storage-control criteria  144 ) defines how much data can be accumulated in memory  112  for each of the parameters, respectively. Depth chart  170  can also define how many instances of each set of data can be accumulated in memory  112 , the instances of each set being sampled at substantially different times, respectively. According to depth chart  170 , collection engine  114  is further configured to accumulate data in memory  112 , e.g., instances of each set of data. 
     Overwrite rule  168  (which is included in storage-control criteria  144 ) defines how space in memory  112  is to be reused, i.e., how data in memory  112  is to be overwritten. According to overwrite rule  168 , collection engine  114  is further configured to overwrite previously-stored instances of data in memory  112  with corresponding newer instances of data. Overwrite rule  168  can be, e.g., FIFO (first in, first out), LIFO (last in, first out), etc. 
     As also briefly introduced above (in the discussion of  FIG. 1A ), periodically, omega engine  108  sends the selected portions of collected data in memory  112  to NIB  106 . Under unusual circumstances, however, it might be desirable to send data sooner, i.e., to not await elapse of a reporting period. Alternatively, under other unusual circumstances, e.g., it might be desirable to collect more data than is typically collected and/or report more data than is typically reported and/or report the same amount of data that is typically reported albeit at a smaller reporting period. 
     To facilitate being responsive to such unusual circumstances, alarm criteria  164  can be included in collection-control criteria  142 . Examples of alarm criteria include one or more alarm thresholds for the parameters sensed by sensors  124 - 140 , respectively. Collection engine  114  can be further configured to analyze the collected data in memory  112  in terms of alarm criteria  164 . If any of alarm criteria  164  are satisfied, then collection engine  114  is further configured to store satisfied ones  165  of alarm criteria  164  in memory  112 . According to depth chart  170 , collection engine  114  is further configured to accumulate one or more instances of satisfied ones  165  of alarm criteria  164  in memory  112 . And according overwrite rule  168 , collection engine  114  is further configured to limit, via selective overwriting, previously-stored instances of satisfied ones  165  of alarm criteria  164  that are accumulated in memory  112 . 
     As omega engine  108  is configured to operate according to criteria  110 , accordingly omega engine  108  is further configured to operate according to retrieval-control criteria  146  and reporting-control criteria  148  (because they are included in criteria  110 ), which omega engine  108  can read from settings repository  122 . 
     More particularly, withdrawal rule  172  (which is included in retrieval-control criteria  146 ) defines which portions of data in memory  112  are to be withdrawn. Withdrawal rule  170  can be, e.g., FIFO (first in, first out), LIFO (last in, first out), etc. Omega engine  108  is further configured to retrieve one or more selected portions  152  of the collected data in memory  112 , e.g., one or more of the instances of one or more of the sets of data in memory  112 , according to withdrawal rule  172 . 
     As noted, omega engine  106  can send selected portions  152  of the collected data to NIB  106  (via messages  118 ). Alternatively, the ultimate destination for selected portions  152  of the collected data might not be NIB  106 , but instead some other device. For example, where network  100  is an MCN, and the range of network  100  has been extended by networking together NIB  106  and another NIB (not illustrated), then the ultimate destination for selected portions  152  of the collected data might be the other NIB rather than NIB  106 . Recipient setting  178  defines which one amongst a plurality of remote hosts (e.g., to continue the example started above, NIB  106  or the other NIB) will receive selected portions  152  of the collected data from omega engine  108 . 
     Frequency-of-initiation setting  174  (which is included in reporting-control criteria  148 ) defines a frequency at or period over which omega engine  108  should initiate establishing a communications session  104 , e.g., for the purpose of performing one or more tasks, at least one of which is reporting portions of collected data. Omega engine  108  is further configured to initiate establishing communications sessions  104  according to frequency-of-initiation setting  174 . 
     Packaging criteria  176  (which are included in reporting-control criteria  148 ) define, e.g., how selected portions  152  of the collected data in memory  112  are to be included in, e.g., formatted into or packaged into, a given instance of message  118 . Omega engine  108  is further configured to configure selected portions  152  of the collected data in memory  112  into a message  118  according to packaging criteria  176 . 
     To further facilitate being responsive to the unusual circumstances discussed above, emergent criteria  180  can be provided. Examples of emergent criteria can include rules (logical constructs) related to alarm thresholds that have been exceeded. For example, an emergent criterion can be a combination of one or more alarm thresholds that were exceeded at substantially the same time, e.g., within a given set of data. For another example, an emergent criterion can be a combination of a given alarm threshold that has been exceed at substantially times, e.g., across different sets of data. 
     Omega engine  108  can be further configured to read satisfied ones  165  of alarm criteria  164  from memory  112 , and analyze the same in terms of emergent criteria  180 . If any of emergent criteria  180  are satisfied, then omega engine  108  is further configured to notify NIB  106  appropriately. Such appropriate notification can include, e.g., not awaiting the elapse of a reporting period before attempting to report to NIB  106 , sending more portions  152  of collected data than are typically sent to NIB  106 , etc. 
     Again, NIB  106  includes an LTE modem (not illustrated) by which to communicate with UE  102  via a wireless communication session  104 . Additionally, NIB  106  further includes computing components (not illustrated), e.g., one or more processor units, one or more communications buses, one or more memories, one or more interfaces, etc. 
     In  FIG. 1B , NIB  106  is illustrated as including an alpha engine  154 , a request handler  158  and a memory  160 . For ease of illustration, communication session  104  is illustrated as terminating in omega engine  108 . Alpha engine  108  and request handler  158  can be implemented, e.g., as executable code stored in one or more of the noted (above) albeit not-illustrated memories in NIB  106  and executed by one or more of the noted (above) albeit not-illustrated processor units of NIB  106 . 
     As NIB  106  can receive selected portions  152  of the collected data from different instances of UE  102 , accordingly memory  160  is configured to include multiple collections of UE-specific collected data. Alpha engine  154  is configured: to receive selected portions  152  of the collected data (via messages  118 ); unpack messages  118 ; and provide portions  156  of the collected data to request handler  158 . Portions  156  can be formatted the same as portions  152 , or differently. Request handler  158  is configured to store portions  156  into one of the collections of data in memory  160  that is specific to the corresponding given instance of UE  102 . 
     As the circumstances of network  100  change with the elapse of time, the multiple collections of UE-specific collected data in memory  160  correspondingly will evolve in substantially real time and in reflection of the change in circumstances. Alpha engine  154  or a separate analytical unit (not illustrated in  FIG. 1B ) can be configured to perform one or more analyses at least upon the data stored in memory  160 . Such an analytical unit, for example, could be included in NIB  106  and implemented, e.g., as executable code stored in one or more of the noted (above) albeit not-illustrated (in  FIG. 1B ) memories in NIB  106  and executed by one or more of the noted (above) albeit not-illustrated (in  FIG. 1B ) processor units of NIB  106 . Relative to the data in memory  160 , such analyses can be based upon only the given collection of data that is specific to UE  102 , or upon the given collection and one or more ones of other-UE-specific collections of data. 
     Based upon such analyses, it may be desirable that refreshed instances of criteria  110  and/or  116  be generated, e.g., by alpha engine  154  or the analytical unit. Such instances are described using the adjective “refreshed” because, at the time of their generation, they are newer than the corresponding instances of criteria  110  and/or  116  stored in settings repository  122 . In other words, at the time of their generation, refreshed instances of criteria  110  and/or  116  are likely to be better adapted to the circumstances confronting UE  102  than are the corresponding instances of criteria  110  and/or  116  stored in settings repository  122 . 
     Alpha engine  154  is further configured to include the refreshed instances of criteria  110  and/or  116  in messages  120  and then to send messages  120  to UE  102  during wireless communication sessions  104 , respectively. Again, omega engine  108  is configured to receive messages  120  and store the refreshed instances of criteria  110  and/or  116  (that were in included in messages  120 , respectively) in settings repository  122 . As such, UE  102  and the operation thereof are dynamically reconfigurable. 
       FIG. 1D  is a communication-layer diagram illustrating the path of flow during communication session  104  between omega engine  108  of UE  102  and alpha engine  154  of NIB  106 , according to an embodiment of the present invention. 
     As noted, omega engine  108  and collection engine  114  can be implemented, e.g., as executable code stored in one or more of the noted (above) albeit not-illustrated memories in UE  102  and executed by one or more of the noted (above) albeit not-illustrated processor units in UE  102 . Alpha engine  108  can be implemented, e.g., as executable code stored in one or more of the noted (above) albeit not-illustrated memories in NIB  106  and executed by one or more of the noted (above) albeit not-illustrated processor units of NIB  106 . Such implementations can conform to the communication-layer diagram of  FIG. 1D . 
     More particularly, each of omega engine  108  and alpha engine  154  can have a stack based (in part) on industry-standard layers. The layers illustrated in  FIG. 1D  represent but one example of combinations of layers that can be included in such stacks, respectively. Such layers, from top to bottom, for example (as illustrated in  FIG. 1D ), can include: a physical layer; an IP layer; a TCP layer or a UDP layer; an HTTP layer or an HTTPS layer; and a RESTful layer. Alternatively, different combinations of layers could be used in the stack, e.g., a stack that includes as few layers as a physical layer, an IP layer, and a TCP or UDP layer. The RESTful layer is a RESTful web service, where REST is the acronym for representational state transfer. RESTful Webservices are different than REST per se. REST is an architectural approach that can be applied to many things. RESTful web services are a specific approach to web services that utilizes restful aspects of HTTP. 
     In addition, the stack of each of omega engine  108  and alpha engine  154  can further include another layer on top of the RESTful layer. For example, the additional layer can be a network-specific messaging protocol that is specific to network  100 . 
       FIG. 2A  is an example of a state diagram for collection engine  114  according to an embodiment of the present invention. 
     Collection engine  114  can include sensor objects to capture data from sensors and store the data into memory  112 . Illustrated in  FIG. 2A  are examples of possible states of an exemplary sensor data object as it operates to collect data from sensors  124 - 140  and store the data in memory  112 . 
     In  FIG. 2A , each sensor object begins by executing its internal initialization methods to prepare for sensor data capture. An optional startup phase may be provided during which the sensor object may initialize any hardware sensors for data capture. Upon the next interval for data collection, a check is made to ensure that sufficient space is available in memory  112 . 
     Once new sensor data is captured, a validation method may be used to determine whether the data should be reported. Packaging of the data is performed by each sensor object before it stores the data into memory  112 . A common set of methods may be called by each sensor data object for storing the packaged data into memory  112 . When a shutdown event occurs, each sensor object must execute any required shutdown methods associated with the gathering of sensor data. 
       FIGS. 2B and 2C  are examples of a state diagrams for omega engine  108  according to embodiments of the present invention, respectively. 
     Illustrated in  FIG. 2B  are examples of possible states of omega engine  108  as it operates to retrieve portions  152  of the collected data stored in memory  112  and report portions  152  via messages  118 . 
     Relative to  FIG. 2B ,  FIG. 2C  is a more detailed illustration of examples of possible states of omega engine  108  as it operates to retrieve portions  152  of the collected data stored in memory  112  and report portions  152  via messages  118 . 
     Variables mentioned in  FIG. 2C  include: pendingmsg; last_datetime; msgpending; purgelist; capture_sequence; mycollection; and foundhandlingagent. The variable pendingmsg represents a buffer (not illustrated) that is being used to build message  118  as portions  152  of collected data are concatenated, e.g., because they represent data sampled at substantially the same time. The variable last_datetime is compared against the current capturesequence portion  152  of collected data record to determine if the next portion  152  of collected data was sampled at substantially the same time and thus should be appended as part of message  118 . 
     The variable msgpending is a Boolean flag to indicate that there is a inchoate message  118 , i.e., an incomplete message  118  for which the assembly of portions  152  has been started but not completed. The variable purgelist is a list of capture_sequence records that provides details on which device data records (e.g., GPS, Telephony, platform, etc.) should be purged after the pendingmsg (an example of message  118 ) has been successfully uploaded to NIB  106  from omega engine  108 . This list also provides the primary key/id of the capture_sequence records that should be purged from memory  112 . 
     The variable capture_sequence represents the current capture sequence record, i.e., the capture sequence record under consideration. The variable mycollection is a list of all sensor objects, reference to which is made to help facilitate determining which sensor object should be used to decode the UE data record referred by the capture_sequence variable. The variable foundhandlingagent represents the sensor object that is handling the current UE data record. 
       FIG. 3A  is a database-schema diagram illustrating an example of possible relationships amongst data collected and then organized into sets thereof by collection engine  114  according to an embodiment of the present invention. 
     As explained above, collection engine  114 , relative to a given one of the groups, is configured to: cull such data for the selected parameters in the group (as defined by subject list  166 ) according to the corresponding collection frequency indicated in frequencies-of-collection list  162  so as to produce resulting sets of data for which the data included therein are sampled, e.g., at substantially the same times, respectively. In  FIG. 3A , an instance of a set is denoted by a table named capture_sequence. 
       FIGS. 3B and 3C  are a flowchart and a corresponding database-schema diagram illustrating an aspect of the operation of collection engine  114 , according to an embodiment of the present invention. 
     Collection engine  114  can be provided with sensor objects which it uses to collect data from sensors  124 - 140 , respectively. As illustrated in  FIG. 3C , for example, such sensor objects include: platform_network( ), platform_device( ), platform_memory( ) and platform_rom( ), which are used to collect data from platform sensor  126 ; location_gps( ), which is used to collect data from position sensor  124 ; power_battery( ), which is used to collect data from sensor  132 ; telephony_4GLTE( ), which is used to collect data from one or more sensors  128 . 
     Illustrated in the flowchart of  FIG. 3B  are steps that collection engine  114  can execute to select a sensor object corresponding to one of sensors  124 - 140 , respectively, from which data are to be collected. 
       FIGS. 3D and 3E  are a flowchart and a message-assembly diagram illustrating an aspect of the operation of omega engine  108 , according to an embodiment of the present invention. 
     Omega engine  108  is further configured to package portions  152  of collected data into messages  118 , e.g., XML-formatted messages. The sensor domains can be provided with corresponding message-component templates (e.g., in XML format, e.g., stored in memory  112 ), respectively. More particularly, omega engine  108  is further configured to populate such message-component templates with corresponding data from memory  112 , and then to combine (e.g., merge) such populated templates. An example of such populating and merging and merging of is illustrated in  FIG. 3E . A message-component template includes one or more keywords (variables), e.g., “% colname %”. Among other things, keywords are replaced with the value from the corresponding data field in the corresponding sensor object. Examples of steps that omega engine  108  can execute in correspondence to  FIG. 3E  are illustrated in  FIG. 3D . In  FIG. 3D , fields bounded by %, e.g., “% apn %,” are replaced with corresponding domain data. 
       FIGS. 3F and 3G  are a flowchart and a database-schema diagram illustrating an aspect of the operation of collection engine  114 , according to an embodiment of the present invention. 
     Illustrated in the flowchart of  FIG. 3F  are steps that collection engine  114  can execute to overwrite data in memory  112 .  FIG. 3G  is database-schema diagram counterpart to the steps of  FIG. 3F . 
       FIGS. 3H, 3I and 3J  are a database-schema diagram, a flowchart and a database-schema diagram, respectively, illustrating an aspect of the operation of collection engine  114 , according to an embodiment of the present invention. 
     Illustrated in the database-schema diagram of  FIG. 3H  is the addition of selected data to memory  112 . Illustrated in the flowchart of  FIG. 3I  are steps that collection engine  114  can execute to write such selected data into memory  112 .  FIG. 33  is database-schema diagram counterpart to the steps of  FIG. 3I . 
     As will be discussed in terms of  FIGS. 4-6 , omega engine  108  and alpha engine  154  exhibit a client-server relationship. More particularly, omega engine  108  and alpha engine  154  exhibit a specific type of client-server relationship, namely a taskee-client—taskor-server, i.e., they relate as taskee-client and taskor-server, respectively. Omega engine  108  is a client that requests alpha engine  154  to serve tasks to it, i.e., to provide it with tasks which either omega engine  108 , collection engine  114  or another component of UE  102  will perform. As such, omega engine  108  is a taskee; hence omega engine  108  is referred to as a taskee-client. As the entity that assigns tasks to another entity, i.e., that is a taskor, alpha engine  154  is referred to as a taskor-server. 
     As a taskee-client, omega engine  108  is further configured to: query the taskor server (alpha engine  154 ) for an unspecified one amongst a plurality of predetermined tasks, with a consequent selection of a given one from amongst the plurality tasks being an action performed by the taskor-server (alpha engine  154 ); receive an indication of the given task from the taskor-server (alpha engine  154 ); facilitate execution of the given task on UE  102 , e.g., via collection engine  114 ; and report execution-results of the given task to the taskor-server (alpha engine  154 ). 
     As a taskor-server, alpha engine  154  is further configured to: receive a query from the taskee-client (omega engine  108 ) for an unspecified one amongst the plurality of tasks; make a selection of a given one from amongst the plurality of predetermined tasks; indicate the selected task to the taskee-client (omega engine  108 ); and receive a report including execution results for the selected task from the taskee-client (omega engine  108 ). 
       FIG. 4  is a flow diagram of interactions that can occur in a taskee-client—taskor-server relationship, according to an embodiment of the present invention. 
     In  FIG. 4 , flow proceeds through four phases: a wait/poll-interval phase  402 ; a connection phase  404 ; an identification phase  406 ; and a task query and delegation phase  408 . Beginning with wait/poll-interval phase  402 , at block  410 , the taskee-client (omega engine  108 ) waits while a connection interval elapses. Flow proceeds from block  410  to block  412 , thereby entering connection phase  404 . At block  412 , the taskee-client (omega engine  108 ) initiates and establishes a communication session  104  with the taskor-server (alpha engine  154 ). 
     Flow proceeds from block  412  to block  414 , thereby entering identification phase  406 . At block  414 , the taskee-client (omega engine  108 ) transmits profile information and a current state of UE  102  to the taskor-server (alpha engine  154 ). Flow proceeds from block  414  to block  416 , where the taskor-server (alpha engine  154 ) receives the profile and current state information regarding taskee-client (omega engine  108 ), and stores the same in memory, e.g., memory  160 . Flow proceeds from block  416  to block  417 , where the taskor-server (alpha engine  154 ) sends a transmission acknowledgment (ACK) to the taskee-client (omega engine  108 ). Flow proceeds from block  417  to block  418 , where the taskee-client (omega engine  108 ) receives the transmission acknowledgment (ACK) from the taskor-server (alpha engine  154 ). 
     Flow proceeds from block  418  to block  420 , thereby entering task query and delegation phase  408 . At block  418 , the taskee-client (omega engine  108 ) queries the taskor-server (alpha engine  154 ) for an unspecified one amongst a plurality of predetermined tasks. Flow proceeds from block  420  to block  422 , where the taskor-server (alpha engine  154 ) receives the query. Flow proceeds from block  422  to block  424 , where the taskor-server (alpha engine  154 ) determines what actions should be executed (e.g., are scheduled to be executed and/or are desirable under the current circumstances) by UE  102  at this time. Flow proceeds from block  424  to block  426 , where the taskor-server (alpha engine  154 ) builds an action request message, i.e., a task, and returns (sends) the task to the taskee-client (omega engine  108 ). Flow proceeds from block  426  to block  428 , where the taskee-client (omega engine  108 ) evaluates the task for which it is the taskee. 
     Flow proceeds from block  428  to decision block  430 , where the taskee-client (omega engine  108 ) decides if the appropriate action for execution of the task is to do nothing. If the outcome of decision block  430  is yes, then flow proceeds from decision block  430  and loops back to block  410 , thereby reentering wait/poll-interval phase  402 . But if the outcome of decision block  430  is no, then flow proceeds from decision block  430  to block  432 , where the taskee-client (omega engine  108 ) dispatches one or more requests to one or more amongst a plurality of handling objects on UE  102  that are appropriate for carrying out the execution of the task. Upon completion of the task by the one or more handling objects, the taskee-client (omega engine  108 ) sends a task-completion message, including a set of results (if any), to the taskor-server (alpha engine  154 ). Flow proceeds from block  432  to block  434 , where the taskor-server (alpha engine  154 ) receives the task-completion message including the set of results (if any). 
     Flow proceeds from block  434  to block  435 , where the taskor-server (alpha engine  154 ) sends a transmission acknowledgment (ACK) to the taskee-client (omega engine  108 ). Flow proceeds from block  434  to block  436 , where the taskee-client (omega engine  108 ) receives the transmission acknowledgment (ACK) from the taskor-server (alpha engine  154 ). Flow proceeds from block  436  and loops back to block  420 . 
       FIG. 5  is an example of a UML (uniform modeling language) sequence diagram, according to an embodiment of the present invention, that is a counterpart to the flowchart of  FIG. 4 . 
       FIG. 6  is an example of a state diagram for a taskee-client (omega engine), according to an embodiment of the present invention. 
     Illustrated in  FIG. 6  are examples of possible states of the taskee-client (omega engine  108 ) as it operates to request and execute tasks from the taskor-server (alpha engine  154 ). 
       FIG. 7  is a block diagram of two instances of node  102 , e.g., instances of UE, and an alternative remote host  706 , according to an embodiment of the present invention. 
     Similar to NIB  106  (discussed above), host  706  can be, e.g., a base station or a network-in-a-box (NIB), respectively, that is operational in a wireless communication network, e.g., a mobile-telephony network or a mobile cellular network (MCN) communication system. Among other things, NIB  706  can communicate wirelessly with multiple instances of node  102  via wireless communication sessions  104 , respectively. Among other things, NIB  106  includes a wireless interface, e.g., an LTE (Long Term Evolution) modem (not illustrated), a WiFi modem (not illustrated), etc., by which to communicate with nodes  102  via wireless communication sessions  104 , respectively. 
     In contrast to NIB  106 , NIB  107  includes an onboard-NIB sensing arrangement  750  that includes components corresponding to those of UE  102 , respectively, including: an alpha engine (taskor server)  754 ; an omega engine  708 ; dynamically reconfigurable criteria  710  by which the operation of omega engine  708  is controlled; a memory  712  to store collected data locally; a sensor-data collection engine  714 ; dynamically reconfigurable criteria  116  by which the operation of collection engine  714  is controlled; operational components, various sensors; etc. Such sensors sense parameters (at least some of which are operational parameters of the operational components) and sample the same to thereby generate data representing the sampled values, respectively. As such, alpha engine  754  not only can receive selected portions of collected data from instances of node  102  via wireless communication sessions  104 , respectively, but can also selected portions of collected data from its onboard-NIB sensing circuitry  750  via one or more wired connections. 
     Alternatively, a client-server computer architecture can include: a first host; and a taskor server executable on the first host. The taskor server can be configured to: receive a query from a taskee client for an unspecified one amongst a plurality of tasks; make a selection of a given one from amongst the plurality of tasks; indicate the selected task to the taskee client; and receive a report including execution results for the selected task from the taskee client. For such an architecture, the receiving of the query, the making of the selection, the indicating of the task and the receiving of the report can comprise an executable loop, with the taskor server being further configured to: receive a request to start a session from the taskee client as a precursor to entering the loop; and receive, during the session but after completion of an n th  iteration of the loop, another query from the taskee client for another unspecified one amongst the plurality of tasks, thereby invoking an (n+1) th  iteration of the loop. Such a taskor server can be further configured to: receive, during the session but after completing the n th  iteration of the loop, an end-session request from the taskee client to end the session; and acknowledge the end-session request thereby causing the taskee client to bring about the end of the session. For example, one of the plurality of tasks is an end-session task, and the taskor server is further configured to: select the end-session task thereby causing the taskee client to bring about the end of the session. Such architecture can further comprise a taskee client executable on the first host and configured to: query the taskor server for an unspecified one amongst a plurality of tasks, a consequent selection of a given one from amongst the plurality tasks being performable by the taskor server; receive an indication of the given task from the taskor server; facilitate execution of the given task on the first host; and report execution-results of the given task to the taskor server. The taskee client can be an omega engine; and the architecture can further comprise: an onboard sensing arrangement including sensors to sample values of parameters, respectively; a memory; and a collection engine configured to selectively collect data representing at least some of the sampled values, respectively, and store the collected data in the memory; and an omega engine configured to retrieve selected portions of the collected data from the memory, and send the selected portions to a remote host. At least one of the collection, the storage, the retrieval and the sending are performable according to one or more reconfigurable collection-control criteria, one or more reconfigurable storage-control criteria, one or more reconfigurable retrieval-control criteria and one or more reconfigurable reporting-control criteria, respectively, stored in the memory. 
     Further in the alternative, a client-server computer architecture can comprise: a first host and a taskee client executable on the first host and configured to: query a taskor server for an unspecified one amongst a plurality of tasks, a consequent selection of a given one from amongst the plurality tasks being performable by the taskor server; receive an indication of the given task from the taskor server; facilitate execution of the given task on the first host; and report execution-results of the given task to the taskor server. The querying for the unspecified task, the receiving the indication, the facilitating of task-execution and the reporting of execution-results can comprise an executable loop, with the taskee client being further configured to: request the taskor server to start a session as a precursor to entering the loop; and query the taskor server, during the session but after completion of an nth iteration of the loop, for another unspecified one amongst the plurality of tasks, thereby invoking an (n+1)th iteration of the loop. The taskee client can be further configured to: transmit to the taskor server, during the session but after completing the nth iteration of the loop, an end-session request for ending the session; receive an acknowledgement of the end-session request from the taskor server; and bring about the end of the session. One of the plurality of tasks can be an end-session task, with the taskee client being further configured to: bring about the end of the session upon receiving the end-session task from the taskor server. 
     The present invention is not limited to the particular embodiments illustrated in the drawings and described above in detail. Those skilled in the art will recognize that other arrangements could be devised. The present invention encompasses every possible combination of the various features of each embodiment disclosed. One or more of the elements described herein with respect to various embodiments can be implemented in a more separated or integrated manner than explicitly described, or even removed or rendered as inoperable in certain cases, as is useful in accordance with a particular application While the present invention has been described with reference to specific illustrative embodiments, modifications and variations of the present invention may be constructed without departing from the spirit and scope of the present invention as set forth in the following claims. 
     While the present invention has been described in the context of a network  100  of wireless parameter-sensing nodes, those skilled in the art will appreciate that the mechanism of the present invention is capable of being implemented and distributed in the form of a computer-usable medium (in a variety of forms) containing computer-executable instructions, and that the present invention applies equally regardless of the particular type of computer-usable medium which is used to carry out the distribution. An exemplary computer-usable medium is coupled to a computer such the computer can read information including the computer-executable instructions therefrom, and (optionally) write information thereto. Alternatively, the computer-usable medium may be integral to the computer. When the computer-executable instructions are loaded into and executed by the computer, the computer becomes an apparatus for practicing the invention. For example, when the computer-executable instructions are loaded into and executed by a general-purpose computer, the general-purpose computer becomes configured thereby into a special-purpose computer. Examples of suitable computer-usable media include: volatile memory such as random access memory (RAM); nonvolatile, hard-coded or programmable-type media such as read only memories (ROMs) or erasable, electrically programmable read only memories (EEPROMs); recordable-type and/or re-recordable media such as floppy disks, hard disk drives, compact discs (CDs), digital versatile discs (DVDs), etc.; and transmission-type media, e.g., digital and/or analog communications links such as those based on electrical-current conductors, light conductors and/or electromagnetic radiation. 
     Although the present invention has been described in detail, those skilled in the art will understand that various changes, substitutions, variations, enhancements, nuances, gradations, lesser forms, alterations, revisions, improvements and knock-offs of the invention disclosed herein may be made without departing from the spirit and scope of the invention in its broadest form.