waashk/dblp huggingface dataset:
an experimental case for simo random access in multi-hop wireless networks. in this paper, we demonstrate that multiple concurrent asynchronous and uncoordinated single-input multiple-output (simo) transmissions can successfully take place even though the respective receivers do not explicitly null out interfering signals. thus motivated, we propose simple modifications to the widely deployed ieee 802.11 mac to enable multiple nonspatially-isolated simo sender-receiver pairs to share the medium. namely, we propose to increase the physical carrier sensing threshold, disable virtual carrier sensing, and enable message in message packet detection.we use experiments to show that while increasing the peak transmission rate, spatial multiplexing schemes such as those employed by the ieee 802.11n are highly non-robust to asynchronous and uncoordinated interferers. in contrast, we show that the proposed multi-flow simo mac scheme alleviates the severe unfairness resulting from uncoordinated transmissions in 802.11 multi-hop networks.
handling triple hidden terminal problems for multi-channel mac in long-delay underwater sensor networks. in this paper, we investigate the multi-channel mac problem in underwater acoustic sensor networks. to reduce hardware cost, only one acoustic transceiver is often preferred on every node. in a single-transceiver multi-channel long-delay underwater network, new hidden terminal problems, namely multi-channel hidden terminal and long-delay hidden terminal (together with the traditional multi-hop hidden terminal problem, we refer to them as "triple hidden terminal problems"), are identified and studied in this paper. based on our findings, we propose a new mac protocol, called cumac, for long delay multi-channel underwater sensor networks. cumac utilizes the cooperation of neighboring nodes for collision detection, and a simple tone device is designed for distributed collision notification, providing better system efficiency while keeping overall cost low. analytical and simulation results show that cumac can greatly improve the system throughput and energy efficiency via effectively solving the complicated triple hidden terminal problems.
risk-aware routing for optical transport networks. a service level agreement (sla) typically specifies the availability a service provider (sp) promises to a customer. in an optical transport network, finding a lightpath for a connection is commonly based on whether the availability of a lightpath availability complies with the connection's sla-requested availability. because of the stochastic nature of network failures, the actual availability of a lightpath over a specific time period is subject to uncertainty, and the sla is usually at risk. we consider the network uncertainty, and study routing to minimize the probability of sla violation. first, we use a single-link model to study sla violation risk (i.e., the probability of sla violation) under different settings. we show that sla violation risk may vary by paths and is affected by other factors (e.g., failure rate, connection holding time, etc.), and hence cannot be simply described by path availability. we then formulate the problem of risk-aware routing in mesh networks, in which routing decisions are dictated by sla violation risk. in particular, we focus on devising a scheme capable of computing lightpath(s) that are likely to successfully accommodate a connection's sla-requested availability. a novel technique is applied to convert links with heterogeneous failure profiles to reference links which capture the main risk features in a relative manner. based on the "reference link" concept, we present a polynomial risk-aware routing scheme using only limited failure information. in addition, we extend our risk-aware routing scheme to incorporate shared path protection (spp) when protection is needed. we evaluate the performance and demonstrate the effectiveness of our schemes in terms of sla violation ratio and, more generally, contrast them with the generic availability-aware approaches.
hand: fast handoff with null dwell time for ieee 802.11 networks. how to reduce the handoff delay and how to make appropriate handoff decisions are two fundamental challenges in designing an effective handoff scheme for 802.11 networks to provide seamless and satisfactory data roaming services to mobile users. in this paper, we propose a unique fast handoff scheme called hand (handoff with null dwell time). hand adopts a novel zero-channel-dwell-time architecture which leverages on the communication backbone between aps to relay the information about wireless channels, and allows the ap (rather than the station) to make appropriate handoff decisions aiming at providing fair service satisfaction to all stations. hand is a software-only solution and compatible with the 802.11 standard without modifying the 802.11 protocol or introducing new wireless frames. we have implemented it in the madwifi device driver and demonstrated its effectiveness via experiments.
characterizing interactive behavior in a large-scale operational iptv environment. we investigate the user viewing activity for broadcast tv, pre-recorded content using digital video recording (dvr) and video on demand (vod) in an ip-based content distribution environment. advanced stream control functions (play, pause, skip, rewind, etc.) provide users with a high level of interactivity, but place demands on the distribution infrastructure (servers, network, home-network) that can be difficult to manage at large scale. to support system design as well as network capacity planning, it is necessary to have a good model of user interaction. using traces from a well-provisioned operational environment with a large user population, we first characterize interactivity for broadcast tv, dvr and vod. we then develop parametric models of individual users stream control operations for vod. our analysis shows that interactive behavior is adequately characterized by two semi-markov models, one for weekdays and another for weekends. we propose a parametric model for the underlying sojourn time distributions and show that it results in a superior fit compared to well known distributions (generalized pareto and weibull). in order to validate that our models faithfully capture user behavior, we compare the workload that a vod server experiences in response to actual traces and synthetic data generated from our proposed models.
tight performance bounds in the worst-case analysis of feed-forward networks. network calculus theory aims at evaluating worstcase performances in communication networks. it provides methods to analyze models where the traffic and the services are constrained by some minimum and/or maximum envelopes (service/arrival curves). while new applications come forward, a challenging and inescapable issue remains open: achieving tight analyzes of networks with aggregate multiplexing. the theory offers efficient methods to bound maximum endto-end delays or local backlogs. however as shown recently, those bounds can be arbitrarily far from the exact worst-case values, even in seemingly simple feed-forward networks (two flows and two servers), under blind multiplexing (i.e. no information about the scheduling policies, except fifo per flow). for now, only a network with three flows and three servers, as well as a tandem network called sink tree, have been analyzed tightly. we describe the first algorithm which computes the maximum end-to-end delay for a given flow, as well as the maximum backlog at a server, for any feed-forward network under blind multiplexing, with concave arrival curves and convex service curves. its computational complexity may look expensive (possibly super-exponential), but we show that the problem is intrinsically difficult (np-hard). fortunately we show that in some cases, like tandem networks with cross-traffic interfering along intervals of servers, the complexity becomes polynomial. we also compare ourselves to the previous approaches and discuss the problems left open.
convergence speed of binary interval consensus. we consider the convergence time for solving the binary interval consensus problem using a distributed algorithm proposed by benezit at al (2009) for computing the quantized average value. in the binary consensus problem, each node initially holds one of two states and the goal for each node is to correctly decide which one of the two states was initially held by a majority of nodes. we derive an upper bound on the expected convergence time that holds for arbitrary connected graphs, which is based on the location of eigenvalues of some contact rate matrices. we instantiate our bound for particular networks of interest, including complete graphs, star-shaped networks, and erdös-rényi random graphs, and in the former two cases compare with alternative computations. we find that for all these examples our bound is of exact order with respect to the number of nodes. we pinpoint the fact that the expected convergence time critically depends on the voting margin defined as the difference between the fraction of the nodes that initially held the majority and the minority states, respectively. we derive an exact relation between the expected convergence time and the voting margin, for some of these graphs, which reveals how the expected convergence time tends to infinity as the voting margin approaches zero. our results provide insights on how the expected convergence time depends on the network topology which can be used for performance evaluation and network design. the results are of interest in the context of peer-to-peer systems; in particular, for sensor networks and distributed databases.
a signal processing view on packet sampling and anomaly detection. anomaly detection methods typically operate on preprocessed traffic traces. firstly, most traffic capturing devices today employ random packet sampling, where each packet is selected with a certain probability, to cope with increasing link speeds. secondly, temporal aggregation, where all packets in a measurement interval are represented by their temporal mean, is applied to transform the traffic trace to the observation timescale of interest for anomaly detection. these preprocessing steps affect the temporal correlation structure of traffic that is used by anomaly detection methods such as kalman filtering or pca, and have thus an impact on anomaly detection performance. prior work has analyzed how packet sampling degrades the accuracy of anomaly detection methods; however, neither theoretical explanations nor solutions to the sampling problem have been provided. this paper makes the following key contributions: (i) it provides a thorough analysis and quantification of how random packet sampling and temporal aggregation modify the signal properties by introducing noise, distortion and aliasing. (ii) we show that aliasing introduced by the aggregation step has the largest impact on the correlation structure. (iii) we further propose to replace the aggregation step with a specifically designed low-pass filter that reduces the aliasing effect. (iv) finally, we show that with our solution applied, the performance of anomaly detection systems can be considerably improved in the presence of packet sampling.
from time domain to space domain: detecting replica attacks in mobile ad hoc networks. a common vulnerability of wireless networks, in particular, the mobile ad hoc network (manet), is their susceptibility to node compromise/physical capture attacks since the wireless devices are often not protected by tamper-resistant hardware due to small form factors and low cost, and can be easily stolen/lost or temporarily controlled by unauthorized entities due to their harsh working environments. a serious consequence of the device capture attack is the node replication attacks in which adversaries deploy a large number of replicas of the compromised/captured nodes throughout the network. replicated nodes have all legitimate security credentials and therefore can launch various insider attacks, or even take over the network easily. they are indeed "attack multipliers" and therefore are extremely destructive to the network. detecting replication attacks is a nontrivial problem in manets due to the challenges resulted from node mobility, cloned/compromised node collusion, and the large number and wide spread of the replicas. existing approaches either fail in mobile environments due to the limitations caused by local views or their dependence on invariant claims such as location and neighbor list, or are constrained by the number, distribution, and colluding activities of the replicas. in this paper, we propose two replication detection schemes (tdd and sdd) to tackle all these challenges from both the time domain and the space domain. our theoretical analysis indicates that tdd and sdd provide high detection accuracy and excellent resilience against smart and colluding replicas, have no restriction on the number and distribution of replicas, and incur low communication/computation overhead. to our best knowledge, tdd and sdd are the only approaches that support mobile networks while place no restrictions on the number and distribution of the cloned frauds and on whether the replicas collude or not.
characterization of non-manipulable and pareto optimal resource allocation strategies for interference coupled wireless systems. this paper investigates the properties of social choice functions that represent resource allocation strategies in interference coupled wireless systems. the allocated resources can be physical layer parameters such as power vectors or antenna weights. strategy proofness and efficiency of social choice functions are used to capture the respective properties of resource allocation strategy outcomes being non-manipulable and pareto optimal. in addition, this paper introduces and investigates the concepts of (strict) intuitive fairness and nonparticipation in interference coupled systems. the analysis indicates certain inherent limitations when designing strategy proof and efficient resource allocation strategies, if the intuitive fairness and nonparticipation are imposed. these restrictions are investigated in an analytical social choice function framework for interference coupled wireless systems. among other results, it is shown that a strategy proof and efficient resource allocation strategy for interference coupled wireless systems cannot simultaneously satisfy continuity and the frequently encountered property of non-participation.
performance modeling and analysis of multi-path routing in integrated fiber-wireless networks. in an integrated fiber and wireless access (fiwi) network, multi-path forwarding may be applied in the wireless subnetwork to improve throughput. due to the delay difference along multiple paths, reordered packets of a flow may arrive at the optical line terminal (olt) waiting for dispatching to the internet, which may deteriorate the tcp performance. as all traffic in a fiwi network is sent out through the olt, the olt serves as a convergence node which naturally makes it possible to resequence packets at the olt before they are sent to the internet. the fundamental difference between resequencing at the end systems and resequencing at an intermediate node (e.g., the olt) is that very tight resequencing delay can be tolerated in the latter. thus, resequencing at the intermediate nodes must be fast enough. in this paper, we propose an integrated flow assignment and resequencing approach which jointly determines the probability of sending packets along each path from the source and needs virtually zero resequencing delay at the olt to reduce the out-of-order probability when packets are injected to the internet from the access network. simulation results validate our analysis and the effectiveness of the proposed integrated flow assignment and resequencing approach.
user-centric network fairness through connection-level control. methods for network resource allocation have mainly focused on establishing fairness among the rates of individual flows. however, since multiple tcp connections in one or many paths can serve a common user, we advocate in this paper a user-centric notion of fairness, which we formulate in the network utility maximization (num) framework. in particular, we develop control laws for the number of connections identified with a certain user, which can include single-path, multipath or more general aggregates of flows, and prove convergence to the optimal resource allocation. this theory applies directly to the case of cooperative users. in the case where connections are generated exogenously by possibly non-cooperative users, we develop admission control policies that ensure both network stability and user-centric fairness.
design and optimization of a tiered wireless access network. although having high potential for broadband wireless access, wireless mesh networks are known to suffer from throughput and fairness problems, and are thus hard to scale to large size. to this end, hierarchical architectures provide a solution to this scalability problem. in this paper, we address the problem of design and optimization of a tiered wireless access network. at the lower tier, mesh routers are clustered based on traffic demands and delay requirements. the cluster heads are equipped with wireless optical transceivers and form the upper tier free space optical (fso) network. we first present a plane sweeping and clustering algorithm aiming to minimize the number of clusters. psc sweeps the network area and captures cluster members under delay and traffic load constraints. we then present an algebraic connectivity-based formulation for fso network topology optimization and develop a greedy edge-appending algorithm that iteratively inserts edges to maximize algebraic connectivity. the proposed algorithms are analyzed and evaluated via simulations, and are shown to be highly effective as compared to the performance bounds derived in this paper.
stimulating cooperation in multi-hop wireless networks using cheating detection system. in multi-hop wireless networks, the mobile nodes usually act as routers to relay packets generated from other nodes. however, selfish nodes do not cooperate but make use of the honest ones to relay their packets, which has negative effect on fairness, security, and performance of the network. in this paper, we propose a novel incentive mechanism to stimulate cooperation in multi-hop wireless networks. fairness can be achieved by using credits to reward the cooperative nodes. the overhead can be significantly reduced by using a cheating detection system (cds) to secure the payment. extensive security analysis demonstrates that the cds can identify the cheating nodes effectively under different cheating strategies. simulation results show that the overhead of the proposed incentive mechanism is incomparable with the existing ones.
on-line pricing of secondary spectrum access with unknown demand function and call length distribution. we consider a wireless provider who caters to two classes of customers, namely primary and secondary users. primary users have long term contracts while secondary users are admitted and priced according to current availability of excess spectrum. secondary users accept an advertised price with a certain probability defined by an underlying demand function. we analyze the problem of maximizing profit gained by admission of secondary users. previous studies in the field usually assume that the demand function is known and that the call length distribution is also known and exponentially distributed. in this paper, we analyze more realistic settings where both of these quantities are unknown. our main contribution is to derive near-optimal pricing strategies under such settings. we focus on occupancy-based pricing policies, which depend only on the total number of ongoing calls in the system. we first show that such policies are insensitive to call length distribution except through the mean. next, we introduce a new on-line, occupancy-based pricing algorithm, called measurement-based threshold pricing (mtp) that operates by measuring the reaction of secondary users to a specific price and does not require the demand function to be known. mtp optimizes a profit function that depends on price only. we prove that while the profit function can be multimodal, mtp converges to one of the local optima as fast as if the function were unimodal. lastly, we provide numerical studies demonstrating the near-optimal performance of occupancy-based policies for diverse sets of call length distributions and demand functions and the quick convergence of mtp to near-optimal on-line profit.
limitations and possibilities of path trading between autonomous systems. when forwarding packets in the internet, autonomous systems (ases) frequently choose the shortest path in their network to the next-hop as in the bgp path, a strategy known as hot-potato routing. as a result, paths in the internet are suboptimal from a global perspective. for peering ases who exchange traffic without payments, path trading - complementary deviations from hot-potato routing - appears to be a desirable solution to deal with these inefficiencies. in recent years, path trading approaches have been suggested as means for interdomain traffic engineering between neighboring ases, as well as between multiple ases to achieve global efficiency. surprisingly, little is known on the computational complexity of finding path trading solutions, or the conditions which guarantee the optimality or even approximability of a path trading protocol. in this paper we explore the computational feasibility of computing path trading solutions between ases. we first show that finding a path trading solution between a pair of ases is np-complete, and that path-trading solutions are even nphard to approximate. we continue to explore the feasibility of implementing policies between multiple ases and show that, even if the bilateral path trading problem is tractable for every as pair in the set of trading ases, path trading between multiple ases is np-hard, and np-hard to approximate as well. despite the above negative results, we show a pseudopolynomial algorithm to compute path trading solutions. thus, if the range of the instances is bounded, we show one can compute solutions efficiently for peering ases. we evaluate the path trading algorithm on pairs of ases using real network topologies. specifically, we use real pop-level maps of ases in the internet to show that path trading can substantially mitigate the inefficiencies associated with hot-potato routing.
joint energy management and resource allocation in rechargeable sensor networks. energy harvesting sensor platforms have opened up a new dimension to the design of network protocols. in order to sustain the network operation, the energy consumption rate cannot be higher than the energy harvesting rate, otherwise, sensor nodes will eventually deplete their batteries. in contrast to traditional network resource allocation problems where the resources are static, time variations in recharging rate presents a new challenge. in this paper, we first explore the performance of an efficient dual decomposition and subgradient method based algorithm, called quickfix, for computing the data sampling rate and routes. however, fluctuations in recharging can happen at a faster time-scale than the convergence time of the traditional approach. this leads to battery outage and overflow scenarios, that are both undesirable due to missed samples and lost energy harvesting opportunities respectively. to address such dynamics, a local algorithm, called snapit, is designed to adapt the sampling rate with the objective of maintaining the battery at a target level. our evaluations using the tossim simulator show that quickfix and snapit working in tandem can track the instantaneous optimum network utility while maintaining the battery at a target level. when compared with ifrc, a backpressure-based approach, our solution improves the total data rate by 42% on the average while significantly improving the network utility.