## 8 Comparative Study  
It is worthwhile to organize and evaluate the aforementioned data collection/dissemination schemes based on their primary goals. The majority of the aforementioned data collection schemes aims to prolong network lifetime by employing single or multiple mobile sinks and are listed in Table 4 in ascending order with respect to constraints they impose on network in order to operate. Similarly, Table 5 and Table 6 provide a comparative study of those data collection/dissemination schemes that address data delivery latency and successful data/packet delivery performance respectively. The idea behind this organization and comparative study is to enable readers interested in a particular goal to evaluate and select appropriate scheme in accordance with their applications and network dynamics. We evaluate and compare each scheme in terms of the following set of features:  
_No. of Sinks_--The performance of a data collection strategy is greatly affected by the number of sinks employed for data gathering. Some schemes employ multiple mobile sinks (or one static sink and multiple mobile sub-sinks) operating in different segments of network at the same time, thereby reducing multi-hop communication [45, 49]. The use of multiple sinks thus results into more energy savings and decreased data delivery latency. It also improves data delivery ratio as packets would be less vulnerable to be dropped due to expiry of TTL. On the downside, the use of multiple sinks not only increases the hardware and operating cost, but also requires tight collaboration among them in order to avoid redundant coverage of overlapped network segments. Another artifact is that if multiple sinks operate independently in the sensor field, it will cause more traffic congestion thereby increasing packet loss ratio and data delivery latency [42, 44]. _Sink Assistants_--Some of the existing schemes make use of several sink assistants. Sink assistants are also considered as less-constrained in terms of resources (energy, storage) and can be either static nodes or mobile entities. In static scenarios, these assistant nodes adopt the responsibility of local data collectors to be approached at a later stage by a mobile sink [23, 27, 28]. In mobile scenarios, they provide simultaneous coverage of various network segments to provide real-time communication services and reduce nodes energy consumption [49, 56]. _Sink Mobility Pattern_--The mobility pattern of a sink greatly affects the data dissemination process. As mentioned before, sink mobility can be random [7, 33, 36, 37, 39, 41, 42, 44], predictable/ deterministic [23, 25, 26, 27, 28, 32], and/or controlled [12, 13, 48, 49, 50, 51, 56]. Sink mobility pattern is dictated by application environment (hostility, terrain), nodes density, and species (animal, human, robot) to which the sink device is attached/mounted. _Sensors_**2014**, _14_  
_Sink Movement Type_--A mobile sink either moves continuously or exhibits discrete mobility thereby making temporary pauses. Many existing data collection schemes impose discrete mobility [12, 13, 25, 32, 35, 36, 42, 48, 49, 50, 56] in order to reduce network control overhead due to sink mobility and improve data delivery performance. _Sink Speed_--It highly depends on to what entity (animal, human, car, airplane) the sink device is being attached. A mobile sink can either move at fixed or variable speed and can be considered as slow (up to 1 m/s), moderate (1 to 20 m/s), or fast (greater than 20 m/s). Sink's speed also affects the performance of data dissemination mechanism; for instance, slow movement of the sink would cause huge delay in data delivery for the father reporting nodes. On the other hand, using a very fast sink would result in frequent link breakages and establishments.