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CostDistance: Two Metric Network Design
 In Proceedings of the 41st Annual IEEE Symposium on Foundations of Computer Science
, 2000
"... Abstract We present the CostDistance problem: finding a Steiner tree which optimizes the sum of edge costs along one metric and the sum of sourcesink distances along an unrelated second metric. We give the first known O(log k) randomized approximation scheme for CostDistance, where k is the numbe ..."
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Cited by 69 (7 self)
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Abstract We present the CostDistance problem: finding a Steiner tree which optimizes the sum of edge costs along one metric and the sum of sourcesink distances along an unrelated second metric. We give the first known O(log k) randomized approximation scheme for CostDistance, where k is the number of sources. We reduce many common network design problems to CostDistance, obtaining (in some cases) the first known logarithmic approximation for them. These problems include singlesink buyatbulk with variable pipe types between different sets of nodes, facility location with buyatbulk type costs on edges, and maybecast with combind cost and distance metrics. Our algorithm is also the algorithm of choice for several previous network design problems, due to its ease of implementation and fast running time. 1 Introduction Consider designing a network from the ground up. We are given a set of customers, and need to place various servers and network links in order to cheaply provide sufficient service. If we only need to place the servers, this becomes the facility location problem and constantapproximations are known. If a single server handles all customers, and we impose the additional constraint that the set of available network link types is the same for every pair of nodes (subject to constant scaling factors on cost) then this is the single sink buyatbulk problem. We give the first known approximation for the general version of this problem with both servers and network links. We reduce the network design problem to an elegant theoretical framework: the CostDistance problem. We are given a graph with a single distinguished sink node (server). Every edge in this graph can be measured along two metrics; the first will be called cost and the second will be length. Note that the two metrics are entirely independent, and that there may be any number of parallel edges in the graph. We are given a set of sources (customers). Our objective is to construct a Steiner tree connecting the sources to the sink while minimizing the combined sum of the cost of the edges in the tree and sum over sources of the weighted length from source to sink.
BMultipath routing for video delivery over bandwidthlimited networks
 IEEE J. Sel. Areas Commun
, 2004
"... Abstract—The delivery of quality video service often requires high bandwidth with low delay or cost in network transmission. Current routing protocols such as those used in the Internet are mainly based on the singlepath approach (e.g., the shortestpath routing). This approach cannot meet the end ..."
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Cited by 35 (3 self)
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Abstract—The delivery of quality video service often requires high bandwidth with low delay or cost in network transmission. Current routing protocols such as those used in the Internet are mainly based on the singlepath approach (e.g., the shortestpath routing). This approach cannot meet the endtoend bandwidth requirement when the video is streamed over bandwidthlimited networks. In order to overcome this limitation, we propose multipath routing, where the video takes multiple paths to reach its destination(s), thereby increasing the aggregate throughput. We consider both unicast (pointtopoint) and multicast scenarios. For unicast, we present an efficient multipath heuristic (of complexity 3)), which achieves high bandwidth with low delay. Given a set of path lengths, we then present and prove a simple data scheduling algorithm as implemented at the server, which achieves the theoretical minimum endtoend delay. For a network with unitcapacity links, the algorithm, when combined with disjointpath routing, offers an exact and efficient solution to meet a bandwidth requirement with minimum delay. For multicast, we study the construction of multiple trees for layered video to satisfy the user bandwidth requirements. We propose two efficient heuristics on how such trees can be constructed so as to minimize the cost of their aggregation subject to a delay constraint. Index Terms—Bandwidthdelay constraints, multicast routing, multipath routing, qualityofservice (QoS) routing, video scheduling. I.
Adaptive Server Selection for Large Scale Interactive Online Games
 ACM Int’l Workshop on Network and Operating Systems Support for Digital Audio and Video (NOSSDAV
, 2004
"... In this paper, we present a novel distributed algorithm that dynamically selects game servers for a group of game clients participating in large scale interactive online games. The goal of server selection is to minimize server resource usage while satisfying the realtime delay constraint. We devel ..."
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Cited by 26 (0 self)
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In this paper, we present a novel distributed algorithm that dynamically selects game servers for a group of game clients participating in large scale interactive online games. The goal of server selection is to minimize server resource usage while satisfying the realtime delay constraint. We develop a synchronization delay model for interactive games and formulate the server selection problem, and prove that the considered problem is NPhard. The proposed algorithm, called zoominzoomout, is adaptive to session dynamics (e.g. clients join and leave) and lets the clients select appropriate servers in a distributed manner such that the number of servers used by the game session is minimized. Using simulation, we present the performance of the proposed algorithm and show that it is simple yet effective in achieving its design goal. In particular, we show that the performance of our algorithm is comparable to that of a greedy selection algorithm, which requires global information and excessive computation.
A Graph Theoretic Approach to Bounding Delay in ProxyAssisted, EndSystem Multicast
 in ProxyAssisted, EndSystem Multicast. In Proc. of IWQoS
, 2002
"... Endsystem multicast provides a lowcost solution to scalably broadcast information to groups of users. However, lastmile bandwidth limitations constrain tree fanouts leading to high endtoend delivery delays. These delays can be reduced if the network provides forwarding proxies with high fanout c ..."
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Cited by 24 (1 self)
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Endsystem multicast provides a lowcost solution to scalably broadcast information to groups of users. However, lastmile bandwidth limitations constrain tree fanouts leading to high endtoend delivery delays. These delays can be reduced if the network provides forwarding proxies with high fanout capabilities at an additional cost. We use simple graph theoretic network models to explore the problem of building hybrid proxy/endsystem application layer multicast trees that meet fixed endtoend delay bounds. Our goal is to meet a fixed delay bound while minimizing costs associated with the utilization of proxies. We provide an algorithm and formally prove its optimality in a fullyconnected overlay network with uniformlength edges. We then adapt this algorithm into a heuristic and evaluate the heuristic for simulated transitstub networks with variabledelay edges. We compare our heuristic in a proxyfree environment to previously developed heuristics and show that our heuristic typically yields further reductions in the maximum session endtoend delay.
DESIGN OF OVERLAY NETWORKS FOR INTERNET MULTICAST
, 2002
"... Multicast is an efficient transmission scheme for supporting group communication in networks. Contrasted with unicast, where multiple pointtopoint connections must be used to support communications among a group of users, multicast is more efficient because each data packet is replicated in the ..."
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Cited by 21 (0 self)
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Multicast is an efficient transmission scheme for supporting group communication in networks. Contrasted with unicast, where multiple pointtopoint connections must be used to support communications among a group of users, multicast is more efficient because each data packet is replicated in the network  at the branching points leading to distinguished destinations, thus reducing the transmission load on the data sources and traffic load on the network links. To implement multicast, networks need to incorporate new routing and forwarding mechanisms in addition to the existing unicast methods. Unfortunately, the necessary functions needed to realize multicast are not adequately supported in the current networks. The IP multicast solution has serious scaling and deployment limitations, and cannot be easily extended to provide more enhanced data services. Furthermore, and perhaps most importantly, IP multicast has ignored the economic nature of the problem, lacking incentives for service providers to deploy the service in wide area networks.
Multipopulation Genetic Algorithms with Immigrants Scheme for Dynamic Shortest Path Routing Problems in Mobile Ad Hoc Networks
"... Abstract. The static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks, genetic algorithms (GAs), particle swarm optimization, etc. However, with the advancement in wireless communications, more and more mobile wireless net ..."
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Cited by 18 (3 self)
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Abstract. The static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks, genetic algorithms (GAs), particle swarm optimization, etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile ad hoc network (MANET), wireless mesh network, etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, that is, the network topology changes over time due to energy conservation or node mobility. Therefore, the SP problem turns out to be a dynamic optimization problem in mobile wireless networks. In this paper, we propose to use multipopulation GAs with immigrants scheme to solve the dynamic SP problem in MANETs which is the representative of new generation wireless networks. The experimental results show that the proposed GAs can quickly adapt to the environmental changes (i.e., the network topology change) and produce good solutions after each change. 1
Extending Greedy Multicast Routing to Delay Sensitive Applications
, 1999
"... Given a weighted undirected graph G(V; E) and a subset R of V , a Steiner tree is a subtree of G that contains each vertex in R. In this paper, we present an online algorithm for nding a Steiner tree that simultaneously approximates the shortest path tree and the minimum weight Steiner tree, when ..."
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Cited by 11 (2 self)
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Given a weighted undirected graph G(V; E) and a subset R of V , a Steiner tree is a subtree of G that contains each vertex in R. In this paper, we present an online algorithm for nding a Steiner tree that simultaneously approximates the shortest path tree and the minimum weight Steiner tree, when the vertices in the set R are revealed in an online fashion. This problem arises naturally while trying to construct sourcebased multicast trees of low cost and good delay. The cost of the tree we construct is within an O(log jRj) factor of the optimal cost, and the path length from the root to any terminal is at most O(1) times the shortest path length. The algorithm needs to perform at most one reroute for each node in the tree. Our algorithm extends the results of Khuller et al.and Awerbuch et al., who looked at the oine problem [9, 2]. We conduct extensive simulations to compare the performance of our algorithm (in terms of cost and delay) with that of two popular multicast ro...
A GeneticInspired Joint Multicast Routing and Channel Assignment Algorithm in Wireless Mesh Networks
"... This paper proposes a genetic algorithm (GA) based optimization approach to search a minimuminterference multicast tree which satisfies the endtoend delay constraint and optimizes the usage of the scarce radio network resource in wireless mesh networks. The pathoriented encoding method is used a ..."
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Cited by 11 (0 self)
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This paper proposes a genetic algorithm (GA) based optimization approach to search a minimuminterference multicast tree which satisfies the endtoend delay constraint and optimizes the usage of the scarce radio network resource in wireless mesh networks. The pathoriented encoding method is used and each chromosome is represented by a tree data structure (i.e., a set of paths). Since we expect the multicast trees on which the minimuminterference channel assignment can be produced, a fitness function that returns the total channel conflict is devised. Crossover and mutation are well designed to adapt to the tree structure. A simple yet effective channel assignment algorithm is proposed to reduce the channel conflict. Simulation results show that the proposed GA based multicast algorithm achieves better performance in terms of both the total channel conflict and the tree cost than that of a well known algorithm. 1
Genetic Algorithms With Immigrants and Memory Schemes for Dynamic Shortest Path Routing Problems in Mobile Ad Hoc Networks
"... Abstract—In recent years, the static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks, genetic algorithms (GAs), particle swarm optimization, etc. However, with the advancement in wireless communications, more and more mob ..."
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Cited by 11 (0 self)
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Abstract—In recent years, the static shortest path (SP) problem has been well addressed using intelligent optimization techniques, e.g., artificial neural networks, genetic algorithms (GAs), particle swarm optimization, etc. However, with the advancement in wireless communications, more and more mobile wireless networks appear, e.g., mobile networks [mobile ad hoc networks (MANETs)], wireless sensor networks, etc. One of the most important characteristics in mobile wireless networks is the topology dynamics, i.e., the network topology changes over time due to energy conservation or node mobility. Therefore, the SP routing problem in MANETs turns out to be a dynamic optimization problem. In this paper, we propose to use GAs with immigrants and memory schemes to solve the dynamic SP routing problem in MANETs. We consider MANETs as target systems because they represent newgeneration wireless networks. The experimental results show that these immigrants and memorybased GAs can quickly adapt to environmental changes (i.e., the network topology changes) and produce highquality solutions after each change. Index Terms—Dynamic optimization problem (DOP), dynamic shortest path routing problem (DSPRP), genetic algorithm (GA), immigrants scheme, memory scheme, mobile ad hoc network (MANET). I.
A learning automatabased heuristic algorithm for solving the minimum spanning tree problem in stochastic graphs
, 2010
"... During the last decades, a host of efficient algorithms have been developed for solving the minimum spanning tree problem in deterministic graphs, where the weight associated with the graph edges is assumed to be fixed. Though it is clear that the edge weight varies with time in realistic applicatio ..."
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Cited by 9 (5 self)
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During the last decades, a host of efficient algorithms have been developed for solving the minimum spanning tree problem in deterministic graphs, where the weight associated with the graph edges is assumed to be fixed. Though it is clear that the edge weight varies with time in realistic applications and such an assumption is wrong, finding the minimum spanning tree of a stochastic graph has not received the attention it merits. This is due to the fact that the minimum spanning tree problem becomes incredibly hard to solve when the edge weight is assumed to be a random variable. This becomes more difficult, if we assume that the probability distribution function of the edge weight is unknown. In this paper, we propose a learning automata‐based heuristic algorithm to solve the minimum spanning tree problem in stochastic graphs wherein the probability distribution function of the edge weight is unknown. The proposed algorithm taking advantage of learning automata determines the edges that must be sampled at each stage. As the presented algorithm proceeds, the sampling process is concentrated on the edges that constitute the spanning tree with the minimum expected weight. The proposed learning automata‐based sampling method decreases the number of samples that need to be taken from the graph by reducing the rate of unnecessary samples. Experimental results show the superiority of the proposed algorithm over the well‐known existing methods both in terms of the number of samples and the running time of algorithm.