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248
A Tutorial on Decomposition Methods for Network Utility Maximization
- IEEE J. SEL. AREAS COMMUN
, 2006
"... A systematic understanding of the decomposability structures in network utility maximization is key to both resource allocation and functionality allocation. It helps us obtain the most appropriate distributed algorithm for a given network resource allocation problem, and quantifies the comparison ..."
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Cited by 185 (4 self)
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A systematic understanding of the decomposability structures in network utility maximization is key to both resource allocation and functionality allocation. It helps us obtain the most appropriate distributed algorithm for a given network resource allocation problem, and quantifies the comparison across architectural alternatives of modularized network design. Decomposition theory naturally provides the mathematical language to build an analytic foundation for the design of modularized and distributed control of networks. In this tutorial paper, we first review the basics of convexity, Lagrange duality, distributed subgradient method, Jacobi and Gauss–Seidel iterations, and implication of different time scales of variable updates. Then, we introduce primal, dual, indirect, partial, and hierarchical decompositions, focusing on network utility maximization problem formulations and the meanings of primal and dual decompositions in terms of network architectures. Finally, we present recent examples on: systematic search for alternative decompositions; decoupling techniques for coupled objective functions; and decoupling techniques for coupled constraint sets that are not readily decomposable.
Optimal Energy Management Policies for Energy Harvesting Sensor Nodes
"... We study a sensor node with an energy harvesting source. The generated energy can be stored in a buffer. The sensor node periodically senses a random field and generates a packet. These packets are stored in a queue and transmitted using the energy available at that time. We obtain energy management ..."
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Cited by 132 (4 self)
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We study a sensor node with an energy harvesting source. The generated energy can be stored in a buffer. The sensor node periodically senses a random field and generates a packet. These packets are stored in a queue and transmitted using the energy available at that time. We obtain energy management policies that are throughput optimal, i.e., the data queue stays stable for the largest possible data rate. Next we obtain energy management policies which minimize the mean delay in the queue. We also compare performance of several easily implementable sub-optimal energy management policies. A greedy policy is identified which, in low SNR regime, is throughput optimal and also minimizes mean delay.
Low-complexity distributed scheduling algorithms for wireless networks
- IEEE/ACM Trans. on Netw
"... Abstract — We consider the problem of distributed scheduling in wireless networks. We present two different algorithms whose performance is arbitrarily close to that of maximal schedules, but which require low complexity due to the fact that they do not necessarily attempt to find maximal schedules. ..."
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Cited by 81 (6 self)
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Abstract — We consider the problem of distributed scheduling in wireless networks. We present two different algorithms whose performance is arbitrarily close to that of maximal schedules, but which require low complexity due to the fact that they do not necessarily attempt to find maximal schedules. The first algorithm requires each link to collect local queue-length information in its neighborhood, and its complexity is independent of the size and topology of the network. The second algorithm is presented for the node-exclusive interference model, does not require nodes to collect queue-length information even in their local neighborhoods, and its complexity depends only on the maximum node degree in the network. I.
On Combining Shortest-Path and Back-Pressure Routing Over Multihop Wireless Networks
, 2008
"... Abstract—Back-pressure based algorithms based on the algorithm by Tassiulas and Ephremides have recently received much attention for jointly routing and scheduling over multihop wireless networks. However a significant weakness of this approach has been in routing, because the traditional back-press ..."
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Cited by 65 (5 self)
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Abstract—Back-pressure based algorithms based on the algorithm by Tassiulas and Ephremides have recently received much attention for jointly routing and scheduling over multihop wireless networks. However a significant weakness of this approach has been in routing, because the traditional back-pressure algorithm explores and exploits all feasible paths between each source and destination. While this extensive exploration is essential in order to maintain stability when the network is heavily loaded, under light or moderate loads, packets may be sent over unnecessarily long routes and the algorithm could be very inefficient in terms of end-to-end delay and routing convergence times. This paper proposes new routing/scheduling back-pressure algorithms that not only guarantees network stability (throughput optimality), but also adaptively selects a set of optimal routes based on shortest-path information in order to minimize average path-lengths between each source and destination pair. Our results indicate that under the traditional back-pressure algorithm, the end-to-end packet delay first decreases and then increases as a function of the network load (arrival rate). This surprising low-load behavior is explained due to the fact that the traditional back-pressure algorithm exploits all paths (including very long ones) even when the traffic load is light. On the otherhand, the proposed algorithm adaptively selects a set of routes according to the traffic load so that long paths are used only when necessary, thus resulting in much smaller end-to-end packet delays as compared to the traditional back-pressure algorithm. I.
Q-CSMA: Queue-length based CSMA/CA algorithms for achieving maximum throughput and low delay in wireless networks
- IN IEEE INFOCOM
, 2010
"... Recently, it has been shown that CSMA-type random access algorithms can achieve the maximum possible throughput in wireless ad hoc networks. However, the delay performance of these algorithms can be quite bad. On the other hand, although some simple heuristics (such as distributed approximations of ..."
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Cited by 64 (6 self)
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Recently, it has been shown that CSMA-type random access algorithms can achieve the maximum possible throughput in wireless ad hoc networks. However, the delay performance of these algorithms can be quite bad. On the other hand, although some simple heuristics (such as distributed approximations of greedy maximal scheduling) can yield much better delay performance for a large set of arrival rates, they may only achieve a fraction of the capacity region in general. In this paper, we propose a discrete-time version of the CSMA-type random access algorithm that allows us to incorporate simple heuristics which lead to very good delay performance while retaining the throughput-optimality property. Central to our results is a discrete-time distributed randomized algorithm that generates data transmission schedules according to a product-form distribution, a counterpart of similar results obtained earlier for continuous-time models under the perfect CSMA assumption where collisions can never occur. An appealing feature of this algorithm is that it explicitly takes collisions into account during the exchange of control packets.
Cross-layer optimization for energy-efficient wireless communications: a survey,” to be published
"... Abstract—Since battery technology has not progressed as rapidly as semiconductor technology, power efficiency has be-come increasingly important in wireless networking, in addition to the traditional quality and performance measures, such as bandwidth, throughput, and fairness. Energy-efficient desi ..."
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Cited by 45 (7 self)
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Abstract—Since battery technology has not progressed as rapidly as semiconductor technology, power efficiency has be-come increasingly important in wireless networking, in addition to the traditional quality and performance measures, such as bandwidth, throughput, and fairness. Energy-efficient design requires a cross layer approach as power consumption is affected by all aspects of system design, ranging from silicon to applica-tions. This article presents a comprehensive overview of recent advances in cross-layer design for energy-efficient wireless com-munications. We particularly focus on a system-based approaches towards energy optimal transmission and resource management across time, frequency, and spatial domains. Details related to energy-efficient hardware implementations are also covered. Index Terms – energy efficiency, cross-layer, wireless commu-nications, energy aware I.
Cross-Layer Latency Minimization in Wireless Networks with SINR Constraints
- MOBIHOC’07, SEPTEMBER 9–14, 2007, MONTREAL, QUEBEC, CANADA
, 2007
"... Recently, there has been substantial interest in the design of cross-
layer protocols for wireless networks. These protocols optimize
certain performance metric(s) of interest (e.g. latency, energy, rate)
by jointly optimizing the performance of multiple layers of the
protocol stack. Algorithm desig ..."
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Cited by 40 (2 self)
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Recently, there has been substantial interest in the design of cross-
layer protocols for wireless networks. These protocols optimize
certain performance metric(s) of interest (e.g. latency, energy, rate)
by jointly optimizing the performance of multiple layers of the
protocol stack. Algorithm designers often use geometric-graph-
theoretic models for radio interference to design such cross-layer
protocols. In this paper we study the problem of designing cross-
layer protocols for multi-hop wireless networks using a more real-
istic Signal to Interference plus Noise Ratio (SINR) model for radio
interference. The following cross-layer latency minimization prob-
lem is studied: Given a set V of transceivers, and a set of source-
destination pairs, (i) choose power levels for all the transceivers, (ii)
choose routes for all connections, and (iii) construct an end-to-end
schedule such that the SINR constraints are satisfied at each time
step so as to minimize the make-span of the schedule (the time
by which all packets have reached their respective destinations).
We present a polynomial-time algorithm with provable worst-case
performance guarantee for this cross-layer latency minimization
problem. As corollaries of the algorithmic technique we show that
a number of variants of the cross-layer latency minimization prob-
lem can also be approximated efficiently in polynomial time. Our
work extends the results of Kumar et al. (Proc. SODA, 2004) and
Moscibroda et al. (Proc. MOBIHOC, 2006). Although our algo-
rithm considers multiple layers of the protocol stack, it can natu-
rally be viewed as compositions of tasks specific to each layer —
this allows us to improve the overall performance while preserving
the modularity of the layered structure.
Distributed CSMA/CA algorithms for achieving maximum throughput in wireless networks
- in Proc. Inf. Theory Appl. Workshop
, 2009
"... Recently, it has been shown that CSMA-type random access algorithms can achieve the maximum throughput in wireless ad hoc networks. Central to these results is a distributed randomized algorithm which selects schedules according a product-form distribution. The product-form distribution is achieved ..."
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Cited by 35 (1 self)
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Recently, it has been shown that CSMA-type random access algorithms can achieve the maximum throughput in wireless ad hoc networks. Central to these results is a distributed randomized algorithm which selects schedules according a product-form distribution. The product-form distribution is achieved by considering a continuous-time Markov model of an idealized CSMA protocol under which collisions cannot occur. In this paper, we present an algorithm which achieves the same product-form distribution in a discrete-time setting where collision of data packets is avoided through the exchange of control messages (however, the control messages are allowed to collide as in the 802.11 suite of protocols). In our discrete-time model, each time slot consists of a few control mini-slots followed by a data slot. We show that two control mini-slots are sufficient for our distributed scheduling algorithm to realize the same steady-state distribution as in the continuous-time case. Thus, the overhead can be as low as twice the ratio of a control mini-slot to a data slot. 1
Optimal Scheduling for Fair Resource Allocation in Ad Hoc Networks with Elastic and Inelastic Traffic
, 907
"... Abstract—This paper studies the problem of congestion control and scheduling in ad hoc wireless networks that have to support a mixture of best-effort and real-time traffic. Optimization and stochastic network theory have been successful in designing architectures for fair resource allocation to mee ..."
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Cited by 33 (4 self)
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Abstract—This paper studies the problem of congestion control and scheduling in ad hoc wireless networks that have to support a mixture of best-effort and real-time traffic. Optimization and stochastic network theory have been successful in designing architectures for fair resource allocation to meet long-term throughput demands. However, to the best of our knowledge, strict packet delay deadlines were not considered in this framework previously. In this paper, we propose a model for incorporating the quality of service (QoS) requirements of packets with deadlines in the optimization framework. The solution to the problem results in a joint congestion control and scheduling algorithm which fairly allocates resources to meet the fairness objectives of both elastic and inelastic flows, and per-packet delay requirements of inelastic flows. I.
Markov Approximation for Combinatorial Network Optimization
"... Many important network design problems can be formulated as a combinatorial optimization problem. A large number of such problems, however, cannot readily be tackled by distributed algorithms. The Markov approximation framework studied in this paper is a general technique for synthesizing distribut ..."
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Cited by 31 (14 self)
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Many important network design problems can be formulated as a combinatorial optimization problem. A large number of such problems, however, cannot readily be tackled by distributed algorithms. The Markov approximation framework studied in this paper is a general technique for synthesizing distributed algorithms. We show that when using the log-sum-exp function to approximate the optimal value of any combinatorial problem, we end up with a solution that can be interpreted as the stationary probability distribution of a class of timereversible Markov chains. Certain carefully designed Markov chains among this class yield distributed algorithms that solve the log-sum-exp approximated combinatorial network optimization problem. By three case studies, we illustrate that Markov approximation technique not only can provide fresh perspective to existing distributed solutions, but also can help us generate new distributed algorithms in various domains with provable performance. We believe the Markov approximation techniques will find application in many network optimization problems, and this paper serves as a call for participation of it.
