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Optimal Backpressure Routing for Wireless Networks with MultiReceiver Diversity
, 2006
"... We consider the problem of optimal scheduling and routing in an adhoc wireless network with multiple traffic streams and time varying channel reliability. Each packet transmission can be overheard by a subset of receiver nodes, with a transmission success probability that may vary from receiver t ..."
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Cited by 60 (8 self)
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We consider the problem of optimal scheduling and routing in an adhoc wireless network with multiple traffic streams and time varying channel reliability. Each packet transmission can be overheard by a subset of receiver nodes, with a transmission success probability that may vary from receiver to receiver and may also vary with time. We develop a simple backpressure routing algorithm that maximizes network throughput and expends an average power that can be pushed arbitrarily close to the minimum average power required for network stability, with a corresponding tradeoff in network delay. The algorithm can be implemented in a distributed manner using only local link error probability information, and supports a “blind transmission” mode (where error probabilities are not required) in special cases when the power metric is neglected and when there is only a single destination for all traffic streams.
Opportunistic Routing with Congestion Diversity in Wireless Multihop Networks
 in Proceedings of the 29th IEEE International Conference on Computer Communication (INFOCOM). Piscataway
, 2010
"... AbstractThis paper considers the problem of routing packets across a multihop network consisting of multiple sources of traffic and wireless links with stochastic reliability while ensuring bounded expected delay. Each packet transmission can be overheard by a random subset of receiver nodes amon ..."
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Cited by 12 (2 self)
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AbstractThis paper considers the problem of routing packets across a multihop network consisting of multiple sources of traffic and wireless links with stochastic reliability while ensuring bounded expected delay. Each packet transmission can be overheard by a random subset of receiver nodes among which the next relay/router is selected opportunistically. The main challenge in the design of minimumdelay routing policies is balancing the tradeoff between routing the packets along the shortest paths to the destination and controlling the congestion and distributing traffic uniformly across the network. Simple opportunistic variants of shortest path routing may, under heavy traffic scenarios, result in severe congestion and unbounded delay. While the opportunistic variants of backpressure, which ensure a bounded expected delay, are known to exhibit extremely poor delay performance at low to medium traffic conditions. Combining important aspects of shortest path routing with those of backpressure routing, this paper provides an opportunistic routing policy with congestion diversity (ORCD). ORCD uses a measure of draining time to opportunistically identify and route packets along the paths with an expected low overall congestion. Using a novel Lyapunov function construction, ORCD is proved to ensure a bounded expected delay for all networks and under any admissible traffic (without any knowledge of traffic statistics). Furthermore, the expected delay encountered by the packets in the network under ORCD is compared against known existing routing policies via simulations and substantial improvements are observed. Finally, the paper proposes practical implementations and discusses criticality of various assumptions in the analysis.
Valuable Detours: LeastCost Anypath Routing
"... In many networks, it is less costly to transmit a packet to any node in a set of neighbors than to one specific neighbor. This observation was previously exploited by opportunistic routing protocols, by using singlepath routing metrics to assign to each node a group of candidate relays for a parti ..."
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Cited by 12 (0 self)
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In many networks, it is less costly to transmit a packet to any node in a set of neighbors than to one specific neighbor. This observation was previously exploited by opportunistic routing protocols, by using singlepath routing metrics to assign to each node a group of candidate relays for a particular destination. This paper addresses the leastcost anypath routing (LCAR) problem: how to assign a set of candidate relays at each node for a given destination such that the expected cost of forwarding a packet to the destination is minimized. The key is the following tradeoff: on one hand, increasing the number of candidate relays decreases the forwarding cost, but on the other, it increases the likelihood of “veering ” away from the shortestpath route. Prior proposals based on singlepath routing metrics or geographic coordinates do not explicitly consider this tradeoff, and as a result do not always make optimal choices. The LCAR algorithm and its framework are general and can be applied to a variety of networks and cost models. We show how LCAR can incorporate different aspects of underlying coordination protocols, for example a linklayer protocol that randomly selects which receiving node will forward a packet, or the possibility that multiple nodes mistakenly forward a packet. In either case, the LCAR algorithm finds the optimal choice of candidate relays that takes into account these properties of the link layer. Finally, we apply LCAR to lowpower, lowrate wireless communication and introduce a new wireless linklayer technique to decrease energy transmission costs in conjunction with anypath routing. Simulations show significant reductions in transmission cost to opportunistic routing using singlepath metrics. Furthermore LCAR routes are more robust and stable than those based on singlepath distances, due to the integrative nature of the LCAR’s route cost metric.
A general class of throughput optimal routing policies in multihop wireless networks. arXiv:0908.1273v1
"... This paper considers the problem of routing packets across a multihop wireless network while ensuring throughput optimality. One of the main challenges in the design of throughput optimal routing policies is identifying appropriate and universal Lyapunov functions with negative expected drift. The ..."
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Cited by 8 (1 self)
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This paper considers the problem of routing packets across a multihop wireless network while ensuring throughput optimality. One of the main challenges in the design of throughput optimal routing policies is identifying appropriate and universal Lyapunov functions with negative expected drift. The few wellknown throughput optimal routing policies in the literature are constructed using simple quadratic or exponential Lyapunov functions of the queue backlogs and as such they do not use any metric of closeness to the destination. Consequently, these routing policies exhibit poor delay performance under many network topologies and traffic conditions. By considering a class of continuous, differentiable, and piecewise quadratic Lyapunov functions, this paper provides a large class of throughput optimal routing policies. The proposed class of Lyapunov functions allow for the routing policies to control the traffic along short paths for a large portion of statespace while ensuring a negative expected drift, hence, enabling the design of routing policies with much improved delay performances. In particular, and in addition to recovering the throughput optimality of the well known backpressure routing policy, an opportunistic routing policy with congestion diversity is proved to be throughput optimal. I.
Achieving Congestion Diversity in Wireless Adhoc Networks
"... Abstract—This work presents the Congestion Diversity Protocol (CDP), a routing protocol for multihop wireless networks that combines important aspects of shortestpath and backpressure routing to achieve improved endend delay performance. In particular, CDP delivers lower endtoend delay and fewe ..."
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Cited by 5 (0 self)
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Abstract—This work presents the Congestion Diversity Protocol (CDP), a routing protocol for multihop wireless networks that combines important aspects of shortestpath and backpressure routing to achieve improved endend delay performance. In particular, CDP delivers lower endtoend delay and fewer packet drops than existing routing protocols while maintaining equivalent throughput. This paper reports on a practical (hardware and software) implementation of CDP in an indoor WiFi network consisting of 12 802.11g nodes. This small testbed enables an imperical comparison of CDP’s performance against a set of state of the art protocols which include both congestion unaware and congestion aware routing protocols. In most topologies and scenarios we consider, CDP provides improvements for UDP traffic with respect to both endend delay and throughput over the existing protocols. I.
Spectrum Leasing via Cooperative Opportunistic Routing Techniques,” submitted to
 IEEE Trans. Wireless Commun
, 2010
"... Abstract—A spectrum leasing strategy is considered for the coexistence of a licensed multihop network and a set of unlicensed nodes. The primary network consists of a source, a destination and a set of additional primary nodes that can act as relays. In addition, the secondary nodes can be used as e ..."
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Cited by 4 (1 self)
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Abstract—A spectrum leasing strategy is considered for the coexistence of a licensed multihop network and a set of unlicensed nodes. The primary network consists of a source, a destination and a set of additional primary nodes that can act as relays. In addition, the secondary nodes can be used as extra relays and hence potential next hops following the principle of opportunistic routing. Secondary cooperation is guaranteed via the “spectrum leasing via cooperation ” mechanism, whereby a cooperating node is granted spectral resources subject to a Quality of Service (QoS) constraint. The objective of this work is to find optimal as well as efficient heuristic routing policies based on the idea outlined above of spectrum leasing via cooperative opportunistic routing. The optimal policy is obtained by casting the problem in the framework of stochastic routing. The optimal performance is then numerically compared with two proposed heuristic routing schemes, which are shown to perform close to optimal solutions and as well being tunable in terms of endtoend throughput vs primary energy consumption. Index Terms—Spectrum leasing, cooperative transmission, opportunistic routing, superposition coding, optimal policies, heuristic routing schemes I.
1Optimal Routing with Mutual Information Accumulation in Wireless Networks
"... Abstract—We investigate optimal routing and scheduling strategies for multihop wireless networks with rateless codes. Rateless codes allow each node of the network to accumulate mutual information with every packet transmission. This enables a significant performance gain over conventional shortest ..."
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Abstract—We investigate optimal routing and scheduling strategies for multihop wireless networks with rateless codes. Rateless codes allow each node of the network to accumulate mutual information with every packet transmission. This enables a significant performance gain over conventional shortest path routing. Further, it also outperforms cooperative communication techniques that are based on energy accumulation. However, it requires complex and combinatorial networking decisions concerning which nodes participate in transmission, and which decode ordering to use. We formulate three problems of interest in this setting: (i) minimum delay routing, (ii) minimum energy routing subject to delay constraint, and (iii) minimum delay broadcast. All of these are hard combinatorial optimization problems and we make use of several structural properties of their optimal solutions to simplify the problems and derive optimal greedy algorithms. Although the reduced problems still have exponential complexity, unlike prior works on such problems, our greedy algorithms are simple to use and do not require solving any linear programs. Further, using the insight obtained from the optimal solution to a line topology, we propose two simple heuristics that can be implemented in polynomial time and in a distributed fashion and compare them with the optimal solution. Simulations suggest that both heuristics perform very close to the optimal solution over random network topologies.
Statistical routing for multihop wireless cognitive networks
 IEEE Journal on Selected Areas in Communications
, 2012
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Optimal Routing with Mutual Information 1 Accumulation in Wireless Networks
"... We investigate optimal routing and scheduling strategies for multihop wireless networks with rateless codes. Rateless codes allow each node of the network to accumulate mutual information with every packet transmission. This enables a significant performance gain over conventional shortest path rou ..."
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We investigate optimal routing and scheduling strategies for multihop wireless networks with rateless codes. Rateless codes allow each node of the network to accumulate mutual information with every packet transmission. This enables a significant performance gain over conventional shortest path routing. Further, it also outperforms cooperative communication techniques that are based on energy accumulation. However, it creates complex and combinatorial networking decisions concerning which nodes participate in transmission, and which decode ordering to use. We formulate three problems of interest in this setting: (i) minimum delay routing, (ii) minimum energy routing subject to delay constraint, and (iii) minimum delay broadcast. All of these are hard combinatorial optimization problems and we make use of several structural properties of their optimal solutions to simplify the problems and derive optimal greedy algorithms. Although the reduced problems still have exponential complexity, unlike prior works on such problems, our greedy algorithms are simple to use and do not require solving any linear programs. Further, using the insight obtained from the optimal solution to a linear network, we propose two simple heuristics that can be implemented in polynomial time in a distributed fashion and compare them with the optimal solution. Simulations suggest that both heuristics perform very close to the optimal solution over random network topologies.
Raytheon BBN Technologies
"... Abstract—Physical phenomena such as temperature, humidity, and wind velocity often exhibit both spatial and temporal correlation. We consider the problem of tracking the extremum value of a spatiotemporally correlated field using a wireless sensor network. Determining the extremum at the fusion cen ..."
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Abstract—Physical phenomena such as temperature, humidity, and wind velocity often exhibit both spatial and temporal correlation. We consider the problem of tracking the extremum value of a spatiotemporally correlated field using a wireless sensor network. Determining the extremum at the fusion center after making all sensor nodes transmitting their measurements is not energyefficient because the spatiotemporal correlation of the field is not exploited. We present an optimal centralized algorithm that utilizes the aforementioned correlation to not only minimize the number of transmitting sensors but also ensure low tracking error with respect to the actual extremum. We use recent order statistics bounds in the formulation of the cost function. Since the centralized algorithm has high time complexity, we propose a suboptimal distributed algorithm based on a modified cost function. Our simulations indicate that a small fraction of sensors is often sufficient to track the extremum, and that the centralized algorithm can achieve about 70 % energy savings with almost perfect tracking. Furthermore, the performance of the distributed algorithm is comparable to that of the centralized algorithm with up to 25 % more energy expenditure. I.