Jimali Software Engineering

In this paper, we study optimal deployment in terms of sensor number needed to achieve four connectivity and full coverage under different ratios of sensors' communication range (denoted by $r_c$) to their sensing range (denoted by $r_s$). We propose a new pattern called the "Diamond" pattern, which can be viewed as a series of evolving patterns. When $r_c/r_s \ge \sqrt{3}$, the Diamond pattern coincides with the well-known triangle lattice pattern; when $r_c/r_s \leq \sqrt{2}$, it degenerates to a "Square" pattern (i.e., square grid). We prove that the pattern we propose is asymptotically optimal when $r_c/r_s \sqrt{2}$ to achieve four connectivity and full coverage. We also discover another new deployment pattern called the ``Double-strip'' pattern. This pattern broadens the research on optimal deployment patterns from a new aspect. Our work is the first to propose an asymptotically optimal deployment pattern to achieve four connectivity and full coverage for WSNs. Our work also provides insights on how optimal patterns evolve and how to search for them.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=8aa282b4ba4ac531cf363f4c4d72afacp=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=8aa282b4ba4ac531cf363f4c4d72afacp=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

For non-cooperative networks in which each node is a selfish agent, certain incentives must be given to intermediate nodes to let them forward the data for others. What makes the scenario worse is that, in a multi-hop non-cooperative network, the endpoints can only observe whether or not the end-to-end transaction was successful or not, but not the individual actions of intermediate nodes. Thus, in the absence of properly designed incentive schemes, rational and selfish intermediate nodes may choose to forward data packets at a very low priority or simply drop the packets, and they could put the blame on the unreliable channel. In this paper, assuming the receiver is a trusted authority, we propose several methods that discourage the hidden actions under hidden information in multi-hop non-cooperative networks with high probability. We design several algorithmic mechanisms for a number of routing scenarios such that each selfish agent will maximize its expected utility (\ie, profit) when it \emph{truthfully} declares its \emph{type} (\ie, cost and its actions) and it truthfully follows its declared actions. Our simulations show that the payments by our mechanisms are only slightly larger than the \emph{actual cost} incurred by all intermediate nodes.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=24f7bd7ee200dc6edb9bdf08bc15fc96p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=24f7bd7ee200dc6edb9bdf08bc15fc96p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Indoor positioning is an enabling technology for delivery of location-based services in mobile computing environments. This paper proposes a positioning solution using received signal strength in indoor Wireless Local Area Networks. In this application, an explicit measurement equation and the corresponding noise statistics are unknown because of the complexity of the indoor propagation channel. To address these challenges, we introduce a new state-space Bayesian filter: the Nonparametric Information (NI) filter. This filter effectively tracks motion in situations where the Kalman filter and its variants are inapplicable, while maintaining a computational complexity comparable to that of the Kalman filter. To deal with the noisy nature of the indoor propagation environment, the NI filter is used in the design of an intelligent dynamic WLAN tracking system. The system anticipates future position values and adapts its sensing and estimation parameters accordingly. Our experimental results conducted on measurements from a real office environment indicate that the combination of the intelligent design and the NI filter results in significant improvements over the Kalman and particle filters.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=69e9b5a78d1c938a876d9be6b201e263p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=69e9b5a78d1c938a876d9be6b201e263p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

We consider a wireless basestation serving users through time-varying channels. It is well-known that opportunistic scheduling with full channel state information (CSI) is throughput-optimal. However, it may not be energy-efficient when the cost of channel acquisition is high and traffic rates are low. Under the low traffic rate regime, it may be sufficient and more energy-efficient to transmit data without CSI, since no channel acquisition power is consumed. In general, we show strategies that probe channels in every slot or never probe channels in any slot are not necessarily optimal, and we must consider mixed strategies. We derive a unified scheduling algorithm that dynamically chooses to transmit data with full or no CSI based on queue backlog and channel statistics. Our methodology is general and can be extended to include timing overhead due to channel acquisition, and to treat systems that allow any subset of channels to be measured. Through Lyapunov analysis, we show our algorithm is throughput-optimal and stabilizes the downlink with optimal power consumption, regardless of the values of channel probing power, transmission power, and data rates. Through simulations, we show our algorithm is energy-efficient by balancing well between earning opportunistic scheduling gains in channel-aware mode and saving channel probing power in channel-blind mode.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=fb40c9f8434d0536c69307ba1518becbp=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=fb40c9f8434d0536c69307ba1518becbp=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Most users in a mobile environment are moving and accessing wireless services for the activities they are currently engaged in. We propose the idea of complex activity for characterizing the continuously changing complex behavior patterns of mobile users. For the purpose of data management, a complex activity is modeled as a sequence of location movement, service requests, the co-occurrence of location and service pair, or the interleaving of all above. An activity may be composed of subactivities. Different activities may exhibit dependencies that affect user behaviors. We argue that the complex activity concept provides a more precise, rich, and detail description of user behavioral patterns which are invaluable for data management in mobile environments. Proper exploration of user activities has the potential of providing much higher quality and personalized services to individual user at the right place and on the right time. We therefore propose new methods for complex activity mining, incremental maintenance, online detection and proactive data management based on user activities. In particular, we devise prefetching and pushing techniques with cost sensitive control to facilitate predictive data allocation. Preliminary implementation and simulation results demonstrate that the proposed framework and techniques can significantly increase local availability, conserve execution cost, reduce response time and improve cache utilization.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=2e89fc50d4f32afe415b697f96567886p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=2e89fc50d4f32afe415b697f96567886p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

In wireless networks, node cooperation is usually exploited as a data relaying mechanism. However, the wireless channel allows for much richer interaction between nodes. In a multi-channel scenario, transmitter-receiver pairs may make incorrect decisions (e.g., in selecting channels) but idle neighbors could help by sharing information to prevent data collisions. This is a Distributed Information SHaring (DISH) approach to cooperation and suggests new ways of designing cooperative protocols. However, what is lacking is a theoretical understanding of this new notion of cooperation. In this paper, we view cooperation as a network resource and evaluate the probability of obtaining cooperation, $p_{co}$. First, we analytically evaluate $p_{co}$ in the context of multi-channel multi-hop wireless networks. Second, we verify the analysis via simulations, showing that our analysis accurately characterizes the behavior of $p_{co}$ as a function of underlying network parameters. Third, we investigate the correlation between $p_{co}$ and network performance in terms of collision rate, packet delay, and throughput. We find a near-linear relationship, which suggests that $p_{co}$ be used as an appropriate performance indicator itself. Finally, we apply our analysis to solving a channel bandwidth allocation problem, where we derive optimal schemes and provide general guidelines on bandwidth allocation for DISH networks.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=b15bc615fdcc199349008e2ee4dff2f4p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=b15bc615fdcc199349008e2ee4dff2f4p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

In a mobile ad hoc network, nodes that are geographically close may need to compete for exclusive access to a shared resource. This paper proposes an abstraction of this problem, called local mutual exclusion; it is an extension to mobile networks of the dining philosophers problem, which has been well-studied in static networks. The desirable feature of an algorithm for this problem is having response time and failure locality independent of the total number of nodes, thus providing a scalable and robust solution. The paper presents two algorithms, exhibiting tradeoffs between simplicity, failure locality and response time. The first algorithm has two variations, one of which has response time that depends very weakly on the number of nodes in the entire system and is polynomial in the maximum number of neighboring nodes; the failure locality, although not optimal, is small and grows very slowly with system size. The second algorithm has optimal failure locality and response time that is quadratic in the number of nodes. A pleasing aspect of the latter algorithm is that when nodes do not move, it has linear response time, improving on previous results for static algorithms with optimal failure locality.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=52c1b653e7c9a9c09efb530945bc123ep=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=52c1b653e7c9a9c09efb530945bc123ep=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

We consider a point-to-multipoint cognitive radio network that shares a set of channels with a primary network. Within the cognitive radio network, a base station controls and supports a set of fixed-location wireless subscribers. The objective is to maximize the throughput of the cognitive network while not affecting the performance of primary users. Both downlink and uplink transmission scenarios in the cognitive network are considered. For both scenarios, we propose two-phase mixed distributed/centralized control algorithms that require minimal cooperation between cognitive and primary devices. In the first phase, a distributed power updating process is employed at the cognitive and primary nodes to maximize the coverage of the cognitive network while always maintaining the constrained signal to interference plus noise ratio of primary transmissions. In the second phase, centralized channel assignment is carried out within the cognitive network to maximize its throughput. Numerical results are obtained for the behaviors and performance of our proposed algorithms.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=e5af60ab6ea4a2f022765b55c7cf7c72p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=e5af60ab6ea4a2f022765b55c7cf7c72p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

The physical layer of future wireless networks will be based on novel radio technologies such as UWB and MIMO. One of the important capabilities of such technologies is the ability to capture a few packets simultaneously. This capability has the potential to improve the performance of the MAC layer. However, we show that in networks with spatially distributed nodes, reusing backoff mechanisms originally designed for narrow-band systems (e.g., CSMA/CA) is inefficient. It is well known that when networks with spatially distributed nodes operate with such MAC protocols, the channel may be captured by nodes that are near the destination, leading to unfairness. We show that when the physical layer enables multipacket reception, the negative implications of reusing the legacy protocols include not only such unfairness but also a significant throughput reduction. We present alternative backoff mechanisms and evaluate their performance via Markovian analysis, approximations, and simulation. We show that our alternative backoff mechanisms can improve both overall throughput and fairness.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=6f51b13f4f2bfb85d0e84bed5808fd77p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=6f51b13f4f2bfb85d0e84bed5808fd77p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Wireless mesh networks are a promising area for the deployment of new wireless communication and networking technologies. In this paper, we address the problem of enabling effective peer-to-peer resource sharing in this type of networks. Starting from the well-known Chord protocol for resource sharing in wired networks, we propose a specialization (called MeshChord) that accounts for peculiar features of wireless mesh networks: namely, the availability of a wireless infrastructure, and the 1-hop broadcast nature of wireless communication. Through extensive packet-level simulations, we show that MeshChord reduces message overhead of as much as 40% with respect to the basic Chord design, while at the same time improving the information retrieval performance. Furthermore, MeshChord information retrieval performance is resilient to the presence of both CBR and TCP background traffic. Overall, the results of our study suggest that MeshChord can be successfully utilized for implementing file/resource sharing applications in wireless mesh networks.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=8e2ce6884019bca5b5cf0ecfc6781cf6p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=8e2ce6884019bca5b5cf0ecfc6781cf6p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

In this paper, we propose an Edge Constrained Localized Delaunay graph, denoted by ECLDel, as the underlying graph for geographic routing in mobile ad hoc and sensor networks. We prove that the ECLDel is a planar t-spanner of the unit-disk graph. Geographic routing on ECLDel is as efficient as on the previous work of PLDel in terms of path length (hop count). However, the construction of ECLDel graph is far more simple and it converges faster. This is because we significantly reduce the number of messages broadcast by each node from five rounds (each round may contain several messages) to only two messages, and we define two new types of edges, the Intersecting Gabriel (IG) edges and the Unaware Intersection (UI) edges, which are constrained in the ECLDel graph. These edges help significantly reduce the size of messages broadcast by each node which reduces the communication cost, and saves the network bandwidth and node power. Our simulation results show that the average number of messages and the average size of messages broadcast by each node is, respectively, 65% and 42% less in the construction of ECLDel than that in the construction of PLDel.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=f6c2234968d25a5cc875d6d01b6f7459p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=f6c2234968d25a5cc875d6d01b6f7459p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

One important application of cooperative communications is to extend coverage area in wireless networks without increasing infrastructure. However a crucial challenge in implementing cooperation protocols is how to select relay-source pairs. In this paper we address this problem based on the knowledge of the users' spatial distribution which determines the channel statistics. We consider two scenarios at the destination node, when the receiver uses MRC and when no-MRC is used. We characterize the optimal relay location to minimize the outage probability. Then we propose and analyze the performance of two schemes: a distributed nearest neighbor relay-assignment, and an infrastructure based relay-assignment protocol. The outage probability of these two schemes are derived. We also derive universal lower bounds on the performance of relay-assignment protocols to serve as a benchmark for our proposed protocols. Numerical results reveal significant gains when applying the proposed simple distributed algorithms over direct transmission in terms of coverage area, transmit power, and spectral efficiency. At 1% outage probability, more than 200% increase in coverage area can be achieved, 7 dBW savings in the transmitted power, and the system can operate at 2 b/s/Hz higher spectral efficiency.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=7c2583bc99da706c0da2d13c92604020p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=7c2583bc99da706c0da2d13c92604020p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Recent years have witnessed the deployments of wireless sensor networks in a class of mission-critical applications such as object detection and tracking. These applications often impose stringent Quality of Service (QoS) requirements including high detection probability, low false alarm rate and bounded detection delay. Although a dense all-static network may initially meet these QoS requirements, it does not adapt to unpredictable dynamics in network conditions (e.g., coverage holes caused by death of nodes) or physical environments (e.g., changed spatial distribution of events). This paper exploits reactive mobility to improve the target detection performance of wireless sensor networks. In our approach, mobile sensors collaborate with static sensors and move reactively to achieve the required detection performance. Specifically, mobile sensors initially remain stationary and are directed to move toward a possible target only when a detection consensus is reached by a group of sensors. The accuracy of final detection result is then improved as the measurements of mobile sensors have higher Signal-to-Noise Ratios after the movement. We develop a sensor movement scheduling algorithm that achieves near-optimal system detection performance under a given detection delay bound. The effectiveness of our approach is validated by extensive simulations using the real data traces collected by 23 sensor nodes.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=8e63239f180c73fdf847a8e693d1e7f1p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=8e63239f180c73fdf847a8e693d1e7f1p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Mobility is the most important component in mobile ad-hoc networks and delay-tolerant networks. We first investigate numerous GPS mobility traces of human mobile nodes and observe super-diffusive behavior in all GPS traces, which is characterized by a 'faster-than-linear' growth rate of the mean square displacement of a mobile node. We then investigate a large amount of access point based traces, and develop a theoretical framework built upon continuous time random walk formalism, in which one can identify the degree of diffusive behavior of mobile nodes even under possibly heavy-tailed pause time distribution, as in the case of reality. We study existing synthetic models and trace based models in term of the capability of producing various degrees of diffusive behavior, and use a set of Levy walk models due to its simplicity and flexibility. In addition, we show that diffusive properties make a huge impact on contact-based metrics and the performance of routing protocols in various scenarios. Our work in this paper thus suggests that the diffusive behavior of mobile nodes should be correctly captured and taken into account for the design and comparison study of network protocols.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=bf284f812c0aebe4d48eed30ecb82b89p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=bf284f812c0aebe4d48eed30ecb82b89p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

A key challenge in the design of real-time wireless multimedia systems is the presence of fading coupled with strict delay constraints. A very effective answer to this problem is the use of diversity achieving techniques to overcome the fading nature of the wireless channels caused by the mobility of the nodes. This paper focuses on comparing systems that exhibit diversity of three forms: source coding diversity, channel coding diversity, and user-cooperation diversity implemented through multi-hop or relay channels with amplify-and-forward or decode-and-forward protocols. Commonly used in multimedia communications, performance is measured in terms of the distortion exponent. For the case of repetition coding at the relay nodes, we prove that having more relays is not always beneficial. For the general case of having a large number of relays that can help the source using repetition coding, the optimum number of relay nodes that maximizes the distortion exponent is determined in this paper. The derived result shows a tradeoff between the quality (resolution) of the source encoder and the amount of cooperation (number of relay nodes). Also, the performances of the channel coding diversity based scheme and the source coding diversity based scheme are compared.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=94756a7e697e3e8a10eb00f96dbe66fep=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=94756a7e697e3e8a10eb00f96dbe66fep=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Handoff is an indispensable operation in wireless mobile networks to guarantee continuous, effective and resilient services during a Mobile Station (MS) mobility. Handoff counting, handoff rate and handoff probability are significant metrics to characterize the handoff performance. Handoff counting defines the number of handoff operations during an active call connection. Handoff rate specifies the expected number of handoff operations during an active call. Handoff probability refers to the probability that an MS will perform a handoff procedure to a neighboring cell before call completion. In the literature, the physical fading channel is not considered in developing these metrics. In addition, the tele-traffic parameters are usually simplified into exponentially distributed variables. In this paper, we develop the formulae for these performance metrics over Rayleigh fading. In particular, the results can demonstrate the explicit relationship between the handoff metrics and the Rayleigh channel characteristics, e.g. carrier frequency, maximum Doppler frequency and fade margin. Furthermore, the formulae are developed with the generalized tele-traffic parameters for the aim of general applicability. The numerical results demonstrate that the fading channel has a substantial impact on all these three metrics. The developed techniques and the results are significant for deploying practical wireless networks and also evaluating the system resilience under unreliable physical link.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=9d41b21c0fdf1cfea56f811fb01ea539p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=9d41b21c0fdf1cfea56f811fb01ea539p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

To satisfy the stringent requirement of capacity enhancement in wireless networks, cooperative relaying is envisioned as one of the most effective solutions. In this paper, we study the capacity enhancement problem by way of Relay Stations (RSs) placement to achieve an efficient and scalable design in broadband wireless access networks. To fully exploit the performance benefits of cooperative relaying, we develop an optimization framework to maximize the capacity as well as meet to the minimal traffic demand by each Subscriber Station (SS). The problem of joint RS placement and bandwidth allocation is formulated into a mixed integer nonlinear program. We reformulate it into an integer linear program which is solvable by CPLEX. To avoid exponential computation time, a heuristic algorithm is proposed to efficiently solve the formulated problem. Numerical analysis is conducted through case studies to demonstrate the performance gain of cooperative relaying and the comparison between the proposed heuristic algorithm against the optimal solutions.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=a3d644a500a38f3c3dc2146bf3c69fd4p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=a3d644a500a38f3c3dc2146bf3c69fd4p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

In mobile ad hoc networks, there are many applications in which mobile users share information, e.g., collaborative rescue operations at a disaster site and exchange of word-of-mouth information in a shopping mall. For such applications, improving data availability is a significant issue and various studies have been conducted with this aim. However, each of these conventional works assumed a particular mobility model and did not fully investigate the influence of the mobility on the proposed approach. In this paper, we aim to quantify the influences of mobility on data availability from various perspectives. We assume neither specific applications nor specific protocols but we propose and quantify several metrics that affect data availability. We also report results of some experiments that measure the proposed metrics assuming several typical mobility models.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=022c016c85c4078e85f91f7e348cc9c1p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=022c016c85c4078e85f91f7e348cc9c1p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

In this work, the stochastic traffic engineering problem in multi-hop cognitive wireless mesh networks is addressed. The challenges induced by the random behaviors of the primary users are investigated in a stochastic network utility maximization framework. For the convex stochastic traffic engineering problem, we propose a fully distributed algorithmic solution which provably converges to the global optimum with probability one. We next extend our framework to the cognitive wireless mesh networks with non-convex utility functions, where a decentralized algorithmic solution, based on learning automata techniques, is proposed. We show that the decentralized solution converges to the global optimum solution asymptotically.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=7721a7eb9da96178feb311c58ae2ade3p=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=7721a7eb9da96178feb311c58ae2ade3p=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/

Capacity has been an important issue for many wireless backhaul networks. Both the multi-hop nature and the large per packet channel access overhead can lead to its low channel efficiency. The problem may get even worse when there are many applications transmitting packets with small data payloads, e.g. Voice over Internet Protocol (VoIP). Previously, the use of multiple parallel channels and employing packet concatenation were treated as separate solutions to these problems. However, there is no available work on the integrated design and performance analysis of a complete scheduler architecture combining these two schemes. In this paper, we propose a scheduler that concatenates small packets into large frames and sends them through multiple parallel channels between neighboring nodes. Besides the expected capacity improvements, we also derive delay bounds for this scheduler. Based on the delay bound formula, call admission control (CAC) of a broad range of scheduling algorithms can be obtained. We demonstrate the significant capacity improvement of this novel design with a voice-data traffic mixing example, via both numerical and simulation results.br clear=both style=clear: both;/ br clear=both style=clear: both;/ a href=http://ads.pheedo.com/click.phdo?s=da45a3fa803c315d246af10aebb2891fp=1img alt= style=border: 0; border=0 src=http://ads.pheedo.com/img.phdo?s=da45a3fa803c315d246af10aebb2891fp=1//a img alt= height=0 width=0 border=0 style=display:none src=http://a.rfihub.com/eus.gif?eui=2225/