Characterizing achievable rates in multi-hop wireless networks

Kodialam, Murali; Nandagopal, Thyaga

doi:10.1145/938985.938991

Cited by 271 publications

(237 citation statements)

References 13 publications

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“…System model. We take inspiration from the multi-commodity network design problem [55], a formulation already applied to throughput and capacity problems in wireless networks [29], [33]. We consider a directed graph (e.g., representing a transportation network) with node set N and arc set A, and a set of commodities C (e.g., goods).…”

Section: System Model and Optimal Solutionmentioning

confidence: 99%

MUSTER: Adaptive Energy-Aware Multisink Routing in Wireless Sensor Networks

Mottola

Picco

2011

IEEE Trans. on Mobile Comput.

102

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Abstract-Wireless sensor networks (WSNs) are increasingly proposed for applications characterized by many-to-many communication, where multiple sources report their data to multiple sinks. Unfortunately, mainstream WSN collection protocols are generally designed to account for a single sink and, dually, WSN multicast protocols optimize communication from a single source.In this paper we present MUSTER, a routing protocol expressly designed for many-to-many communication. First, we devise an analytical model to compute, in a centralized manner, the optimal solution to the problem of simultaneously routing from multiple sources to multiple sinks. Next, we illustrate heuristics approximating the optimal solution in a distributed setting, and their implementation in MUSTER. To increase network lifetime, MUSTER minimizes the number of nodes involved in many-tomany routing and balances their forwarding load. We evaluate MUSTER in emulation and in a real WSN testbed. Results indicate that our protocol builds near-optimal routing paths, doubles the WSN lifetime, and overall delivers to the user 2.5 times the amount of raw data w.r.t. mainstream protocols. Moreover, MUSTER is intrinsically amenable to in-network aggregation, pushing the improvements up to a 180% increase in lifetime and a 4-time increase in data yield.

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Section: System Model and Optimal Solutionmentioning

confidence: 99%

MUSTER: Adaptive Energy-Aware Multisink Routing in Wireless Sensor Networks

Mottola

Picco

2011

IEEE Trans. on Mobile Comput.

102

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“…[21] studies 27 joint congestion control and media access control for ad hoc wireless network, and formulates rate allocation as a utility maximization problem with the constraints that arise from contention for channel access. [22] uses a similar model to study this problem by jointly routing the flows and scheduling the transmissions to determine the achievable rates in multi-hop wireless networks. To sum up, all these works focus on the interaction between link and network layers, and try to characterize the achievable rate region at network layer.…”

Section: Related Workmentioning

confidence: 99%

Cross-layer rate control, medium access control and routing design in cooperative VANET

Zhou¹,

Zheng²,

Geller³

et al. 2008

Computer Communications

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In this paper, we address the rate control, the Medium Access Control (MAC) and the routing problem for cooperative Vehicular Ad-Hoc Network (VANET) in the framework of cross-layer design. At first, we introduce the cooperative communication conception to VANET, and propose an opportunistic cooperation strategy to improve the system performance. And then, we develop a cross-layer solution which consists of the link capacity detection with adjusting persistence probability at the MAC Layer, the flow rate control with the maximal utility at the Transport Layer and the routing design at the Network Layer. This proposal is designed in distributed manner in order to support a simple and efficient implementation for VANET. Furthermore, some practical issues, such as fairness and network cost, are presented for implementing the proposed solution and improving the system performance. Simulation results show that the proposed opportunistic cooperation strategy combined with joint control algorithm achieves the desired performance over VANET.

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“…The third constraint is the node capacity constraint in which the sum of the ingoing and outgoing flows should be less than the channel capacity. This is a necessary condition for scheduling feasibility [7]. Note that the node capacity constraint does not include any interference terms thanks to the beamforming antennas.…”

Section: The Lp Formulationmentioning

confidence: 99%

“…al. [7] studied the joint routing and scheduling problem to achieve a given rate vector. In the context of smart antennas, Yi et.…”

Section: Introductionmentioning

confidence: 99%

Multi-commodity Flow Problem for Multi-hop Wireless Networks with Realistic Smart Antenna Model

Bazan

Jaseemuddin

2008

NETWORKING 2008 Ad Hoc and Sensor Networks, Wireless Networks, Next Generation Internet

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Abstract. Utilizing smart antennas in multi-hop wireless networks can boost their performance. However, most of the work done in the context of wireless adhoc and sensor networking assume ideal or over-simplistic antenna patterns that overrate the performance benefits. In this paper, we compute the optimal throughput of multi-hop wireless networks with realistic smart antenna model. Our goal is to evaluate the network performance degradation using real smart antenna as compared to using the ideal model. We derive a generic interference model that can accommodate any antenna radiation pattern. We formulate the problem as a multi-commodity flow problem with novel interference constraints derived from our generic interference model. Our numerical results show that using a real-world smart antenna in a dense network results in up to 55% degradation in the throughput as compared to the case of ideal flat-topped antenna, whereas the throughput degradation is as much as 37% in a sparse network.

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Characterizing achievable rates in multi-hop wireless networks

Cited by 271 publications

References 13 publications

MUSTER: Adaptive Energy-Aware Multisink Routing in Wireless Sensor Networks

MUSTER: Adaptive Energy-Aware Multisink Routing in Wireless Sensor Networks

Cross-layer rate control, medium access control and routing design in cooperative VANET

Multi-commodity Flow Problem for Multi-hop Wireless Networks with Realistic Smart Antenna Model

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