989 resultados para multihop networks
Resumo:
We consider the problem of joint routing, scheduling and power control in a multihop wireless network when the nodes have multiple antennas. We focus on exploiting the multiple degrees-of-freedom available at each transmitter and receiver due to multiple antennas. Specifically we use multiple antennas at each node to form multiple access and broadcast links in the network rather than just point to point links. We show that such a generic transmission model improves the system performance significantly. Since the complexity of the resulting optimization problem is very high, we also develop efficient suboptimal solutions for joint routing, scheduling and power control in this setup.
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In this paper, space-shift keying (SSK) is considered for multihop multiple-input-multiple-output (MIMO) networks. In SSK, only one among n(s) = 2(m) available transmit antennas, chosen on the basis of m information bits, is activated during transmission. We consider two different systems of multihop co-operation, where each node has multiple antennas and employs SSK. In system I, a multihop diversity relaying scheme is considered. In system II, a multihop multibranch relaying scheme is considered. In both systems, we adopt decode-and-forward (DF) relaying, where each relay forwards the signal only when it correctly decodes. We analyze the end-to-end bit error rate (BER) and diversity order of both the systems with SSK. For binary SSK (n(s) = 2), our analytical BER expression is exact, and our numerical results show that the BERs evaluated through the analytical expression overlap with those obtained through Monte Carlo simulations. For nonbinary SSK (n(s) > 2), we derive an approximate BER expression, where the analytically evaluated BER results closely follow the simulated BER results. We show the comparison of the BERs of SSK and conventional phase-shift keying (PSK) and also show the instances where SSK outperforms PSK. We also present the diversity analyses for SSK in systems I and II, which predict the achievable diversity orders as a function of system parameters.
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Clustering combined with multihop communication is a promising solution to cope with the energy requirements of large scale Wireless Sensor Networks. In this work, a new cluster based routing protocol referred to as Energy Aware Cluster-based Multihop (EACM) Routing Protocol is introduced, with multihop communication between cluster heads for transmitting messages to the base station and direct communication within clusters. We propose EACM with both static and dynamic clustering. The network is partitioned into near optimal load balanced clusters by using a voting technique, which ensures that the suitability of a node to become a cluster head is determined by all its neighbors. Results show that the new protocol performs better than LEACH on network lifetime and energy dissipation
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Wireless-communication technology can be used to improve road safety and to provide Internet access inside vehicles. This paper proposes a cross-layer protocol called coordinated external peer communication (CEPEC) for Internet-access services and peer communications for vehicular networks. We assume that IEEE 802.16 base stations (BS) are installed along highways and that the same air interface is equipped in vehicles. Certain vehicles locating outside of the limited coverage of their nearest BSs can still get access to the Internet via a multihop route to their BSs. For Internet-access services, the objective of CEPEC is to increase the end-to-end throughput while providing a fairness guarantee in bandwidth usage among road segments. To achieve this goal, the road is logically partitioned into segments of equal length. A relaying head is selected in each segment that performs both local-packet collecting and aggregated packets relaying. The simulation results have shown that the proposed CEPEC protocol provides higher throughput with guaranteed fairness in multihop data delivery in vehicular networks when compared with the purely IEEE 802.16-based protocol.
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Cellular networks have been widely used to support many new audio-and video-based multimedia applications. The demand for higher data rate and diverse services has driven the research on multihop cellular networks (MCNs). With its ad hoc network features, an MCN can offer many additional advantages, such as increased network throughput, scalability and coverage. However, providing ad hoc capability to MCNs is challenging as it may require proper wireless interfaces. In this article, the architecture of IEEE 802.16 network interface to provide ad hoc capability for MCNs is investigated, with its focus on the IEEE 802.16 mesh networking and scheduling. Several distributed routing algorithms based on network entry mechanism are studied and compared with a centralized routing algorithm. It is observed from the simulation results that 802.16 mesh networks have limitations on providing sufficient bandwidth for the traffic from the cellular base stations when a cellular network size is relatively large. © 2007 IEEE.
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Medium access control (MAC) protocols have a large impact on the achievable system performance for wireless ad hoc networks. Because of the limitations of existing analytical models for ad hoc networks, many researchers have opted to study the impact of MAC protocols via discreteevent simulations. However, as the network scenarios, traffic patterns and physical layer techniques may change significantly, simulation alone is not efficient to get insights into the impacts of MAC protocols on system performance. In this paper, we analyze the performance of IEEE 802.11 distributed coordination function (DCF) in multihop network scenario. We are particularly interested in understanding how physical layer techniques may affect the MAC protocol performance. For this purpose, the features of interference range is studied and taken into account of the analytical model. Simulations with OPNET show the effectiveness of the proposed analytical approach. Copyright 2005 ACM.
Resumo:
In this paper, we investigate the hop distance optimization problem in ad hoc networks where cooperative multiinput- single-output (MISO) is adopted to improve the energy efficiency of the network. We first establish the energy model of multihop cooperative MISO transmission. Based on the model, the energy consumption per bit of the network with high node density is minimized numerically by finding an optimal hop distance, and, to get the global minimum energy consumption, both hop distance and the number of cooperating nodes around each relay node for multihop transmission are jointly optimized. We also compare the performance between multihop cooperative MISO transmission and single-input-single-output (SISO) transmission, under the same network condition (high node density). We show that cooperative MISO transmission could be energyinefficient compared with SISO transmission when the path-loss exponent becomes high. We then extend our investigation to the networks with varied node densities and show the effectiveness of the joint optimization method in this scenario using simulation results. It is shown that the optimal results depend on network conditions such as node density and path-loss exponent, and the simulation results are closely matched to those obtained using the numerical models for high node density cases.
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Today's wireless networks rely mostly on infrastructural support for their operation. With the concept of ubiquitous computing growing more popular, research on infrastructureless networks have been rapidly growing. However, such types of networks face serious security challenges when deployed. This dissertation focuses on designing a secure routing solution and trust modeling for these infrastructureless networks. ^ The dissertation presents a trusted routing protocol that is capable of finding a secure end-to-end route in the presence of malicious nodes acting either independently or in collusion, The solution protects the network from active internal attacks, known to be the most severe types of attacks in an ad hoc application. Route discovery is based on trust levels of the nodes, which need to be dynamically computed to reflect the malicious behavior in the network. As such, we have developed a trust computational model in conjunction with the secure routing protocol that analyzes the different malicious behavior and quantifies them in the model itself. Our work is the first step towards protecting an ad hoc network from colluding internal attack. To demonstrate the feasibility of the approach, extensive simulation has been carried out to evaluate the protocol efficiency and scalability with both network size and mobility. ^ This research has laid the foundation for developing a variety of techniques that will permit people to justifiably trust the use of ad hoc networks to perform critical functions, as well as to process sensitive information without depending on any infrastructural support and hence will enhance the use of ad hoc applications in both military and civilian domains. ^
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A Wireless Sensor Network (WSN) is a set of sensors that are integrated with a physical environment. These sensors are small in size, and capable of sensing physical phenomena and processing them. They communicate in a multihop manner, due to a short radio range, to form an Ad Hoc network capable of reporting network activities to a data collection sink. Recent advances in WSNs have led to several new promising applications, including habitat monitoring, military target tracking, natural disaster relief, and health monitoring. The current version of sensor node, such as MICA2, uses a 16 bit, 8 MHz Texas Instruments MSP430 micro-controller with only 10 KB RAM, 128 KB program space, 512 KB external ash memory to store measurement data, and is powered by two AA batteries. Due to these unique specifications and a lack of tamper-resistant hardware, devising security protocols for WSNs is complex. Previous studies show that data transmission consumes much more energy than computation. Data aggregation can greatly help to reduce this consumption by eliminating redundant data. However, aggregators are under the threat of various types of attacks. Among them, node compromise is usually considered as one of the most challenging for the security of WSNs. In a node compromise attack, an adversary physically tampers with a node in order to extract the cryptographic secrets. This attack can be very harmful depending on the security architecture of the network. For example, when an aggregator node is compromised, it is easy for the adversary to change the aggregation result and inject false data into the WSN. The contributions of this thesis to the area of secure data aggregation are manifold. We firstly define the security for data aggregation in WSNs. In contrast with existing secure data aggregation definitions, the proposed definition covers the unique characteristics that WSNs have. Secondly, we analyze the relationship between security services and adversarial models considered in existing secure data aggregation in order to provide a general framework of required security services. Thirdly, we analyze existing cryptographic-based and reputationbased secure data aggregation schemes. This analysis covers security services provided by these schemes and their robustness against attacks. Fourthly, we propose a robust reputationbased secure data aggregation scheme for WSNs. This scheme minimizes the use of heavy cryptographic mechanisms. The security advantages provided by this scheme are realized by integrating aggregation functionalities with: (i) a reputation system, (ii) an estimation theory, and (iii) a change detection mechanism. We have shown that this addition helps defend against most of the security attacks discussed in this thesis, including the On-Off attack. Finally, we propose a secure key management scheme in order to distribute essential pairwise and group keys among the sensor nodes. The design idea of the proposed scheme is the combination between Lamport's reverse hash chain as well as the usual hash chain to provide both past and future key secrecy. The proposal avoids the delivery of the whole value of a new group key for group key update; instead only the half of the value is transmitted from the network manager to the sensor nodes. This way, the compromise of a pairwise key alone does not lead to the compromise of the group key. The new pairwise key in our scheme is determined by Diffie-Hellman based key agreement.
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We study the performance of greedy scheduling in multihop wireless networks where the objective is aggregate utility maximization. Following standard approaches, we consider the dual of the original optimization problem. Optimal scheduling requires selecting independent sets of maximum aggregate price, but this problem is known to be NP-hard. We propose and evaluate a simple greedy heuristic. We suggest how the greedy heuristic can be implemented in a distributed manner. We evaluate an analytical bound in detail, for the special case of a line graph and also provide a loose bound on the greedy heuristic for the case of an arbitrary graph.
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We consider a scenario in which a wireless sensor network is formed by randomly deploying n sensors to measure some spatial function over a field, with the objective of computing a function of the measurements and communicating it to an operator station. We restrict ourselves to the class of type-threshold functions (as defined in the work of Giridhar and Kumar, 2005), of which max, min, and indicator functions are important examples: our discussions are couched in terms of the max function. We view the problem as one of message-passing distributed computation over a geometric random graph. The network is assumed to be synchronous, and the sensors synchronously measure values and then collaborate to compute and deliver the function computed with these values to the operator station. Computation algorithms differ in (1) the communication topology assumed and (2) the messages that the nodes need to exchange in order to carry out the computation. The focus of our paper is to establish (in probability) scaling laws for the time and energy complexity of the distributed function computation over random wireless networks, under the assumption of centralized contention-free scheduling of packet transmissions. First, without any constraint on the computation algorithm, we establish scaling laws for the computation time and energy expenditure for one-time maximum computation. We show that for an optimal algorithm, the computation time and energy expenditure scale, respectively, as Theta(radicn/log n) and Theta(n) asymptotically as the number of sensors n rarr infin. Second, we analyze the performance of three specific computation algorithms that may be used in specific practical situations, namely, the tree algorithm, multihop transmission, and the Ripple algorithm (a type of gossip algorithm), and obtain scaling laws for the computation time and energy expenditure as n rarr infin. In particular, we show that the computation time for these algorithms scales as Theta(radicn/lo- g n), Theta(n), and Theta(radicn log n), respectively, whereas the energy expended scales as , Theta(n), Theta(radicn/log n), and Theta(radicn log n), respectively. Finally, simulation results are provided to show that our analysis indeed captures the correct scaling. The simulations also yield estimates of the constant multipliers in the scaling laws. Our analyses throughout assume a centralized optimal scheduler, and hence, our results can be viewed as providing bounds for the performance with practical distributed schedulers.
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We consider a network in which several service providers offer wireless access to their respective subscribed customers through potentially multihop routes. If providers cooperate by jointly deploying and pooling their resources, such as spectrum and infrastructure (e.g., base stations) and agree to serve each others' customers, their aggregate payoffs, and individual shares, may substantially increase through opportunistic utilization of resources. The potential of such cooperation can, however, be realized only if each provider intelligently determines with whom it would cooperate, when it would cooperate, and how it would deploy and share its resources during such cooperation. Also, developing a rational basis for sharing the aggregate payoffs is imperative for the stability of the coalitions. We model such cooperation using the theory of transferable payoff coalitional games. We show that the optimum cooperation strategy, which involves the acquisition, deployment, and allocation of the channels and base stations (to customers), can be computed as the solution of a concave or an integer optimization. We next show that the grand coalition is stable in many different settings, i.e., if all providers cooperate, there is always an operating point that maximizes the providers' aggregate payoff, while offering each a share that removes any incentive to split from the coalition. The optimal cooperation strategy and the stabilizing payoff shares can be obtained in polynomial time by respectively solving the primals and the duals of the above optimizations, using distributed computations and limited exchange of confidential information among the providers. Numerical evaluations reveal that cooperation substantially enhances individual providers' payoffs under the optimal cooperation strategy and several different payoff sharing rules.
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We have developed SmartConnect, a tool that addresses the growing need for the design and deployment of multihop wireless relay networks for connecting sensors to a control center. Given the locations of the sensors, the traffic that each sensor generates, the quality of service (QoS) requirements, and the potential locations at which relays can be placed, SmartConnect helps design and deploy a low-cost wireless multihop relay network. SmartConnect adopts a field interactive, iterative approach, with model based network design, field evaluation and relay augmentation performed iteratively until the desired QoS is met. The design process is based on approximate combinatorial optimization algorithms. In the paper, we provide the design choices made in SmartConnect and describe the experimental work that led to these choices. Finally, we provide results from some experimental deployments.