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On routing in VLSI design and communication networks
 Discrete Applied Mathematics
"... In this paper, we study the global routing problem in VLSI design and the multicast routing problem in communication networks. We first propose new and realistic models for both problems. In the global routing problem in VLSI design, we are given a lattice graph and subsets of the vertex set. The g ..."
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In this paper, we study the global routing problem in VLSI design and the multicast routing problem in communication networks. We first propose new and realistic models for both problems. In the global routing problem in VLSI design, we are given a lattice graph and subsets of the vertex set. The goal is to generate trees spanning these vertices in the subsets to minimize a linear combination of overall wirelength (edge length) and the number of bends of trees with respect to edge capacity constraints. In the multicast routing problem in communication networks, a graph is given to represent the network, together with subsets of the vertex set. We are required to find trees to span the given subsets and the overall edge length is minimized with respect to capacity constraints. Both problems are APXhard. We present the integer linear programming formulation of both problems and solve the linear programming (LP) relaxations by the fast approx
The Constrained Virtual Steiner Arborescence Problem: Formal Definition, SingleCommodity Integer Programming Formulation and Computational Evaluation
, 2013
"... Abstract. As the Internet becomes more virtualized and softwaredefined, new functionality is introduced in the network core: the distributed resources available in ISP central offices, universal nodes, or datacenter middleboxes can be used to process (e.g., filter, aggregate or duplicate) data. Bas ..."
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Abstract. As the Internet becomes more virtualized and softwaredefined, new functionality is introduced in the network core: the distributed resources available in ISP central offices, universal nodes, or datacenter middleboxes can be used to process (e.g., filter, aggregate or duplicate) data. Based on this new networking paradigm, we formulate the Constrained Virtual Steiner Arborescence Problem (CVSAP) which asks for optimal locations to perform innetwork processing, in order to jointly minimize processing costs and network traffic while respecting link and node capacities. We prove that CVSAP cannot be approximated (unless NP = P), and accordingly, develop the exact algorithm VirtuCast to compute optimal solutions to CVSAP. VirtuCast consists of: (1) a compact singlecommodity flow Integer Programming (IP) formulation; (2) a flow decomposition algorithm to reconstruct individual routes from the IP solution. The compactness of the IP formulation allows for computing lower bounds even on large instances quickly, speeding up the algorithm. We rigorously prove VirtuCast’s correctness. To complement our theoretical findings, we have implemented VirtuCast and present an extensive computational evaluation, showing that VirtuCast can solve realistically sized instances (close to) optimality. We show that VirtuCast significantly improves upon naive multicommodity formulations and also initiate the study of primal heuristics to generate feasible solutions during the branchandbound process. 1
VirtuCast: Multicast and Aggregation with InNetwork Processing An Exact SingleCommodity Algorithm
"... Abstract. As the Internet becomes more virtualized and softwaredefined, new functionality is introduced in the network core: the distributed resources available in ISP central offices, universal nodes, or datacenter middleboxes can be used to process (e.g., filter, aggregate or duplicate) data. Bas ..."
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Cited by 2 (2 self)
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Abstract. As the Internet becomes more virtualized and softwaredefined, new functionality is introduced in the network core: the distributed resources available in ISP central offices, universal nodes, or datacenter middleboxes can be used to process (e.g., filter, aggregate or duplicate) data. Based on this new networking paradigm, we formulate the Constrained Virtual Steiner Arborescence Problem (CVSAP) which asks for optimal locations to perform innetwork processing, in order to jointly minimize processing costs and network traffic while respecting link and node capacities. We prove that CVSAP cannot be approximated (unless NP ⊆ P), and accordingly, develop the exact algorithm VirtuCast to compute optimal solutions to CVSAP. VirtuCast consists of: (1) a compact singlecommodity flow Integer Programming (IP) formulation; (2) a flow decomposition algorithm to reconstruct individual routes from the IP solution. The compactness of the IP formulation allows for computing lower bounds even on large instances quickly, speeding up the algorithm significantly. We rigorously prove VirtuCast’s correctness and show its applicability to solve realistically sized instances close to optimality.
Article A Local Energy Consumption PredictionBased Clustering Protocol for Wireless Sensor Networks
, 2014
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Approximate Multiple Count in Wireless Sensor Networks
"... Abstract—COUNT is a typical aggregation operation in Wireless Sensor Networks (WSNs). In such an operation, the total number of the items which are of the same kind is obtained and only one numerical value is returned as the result. This paper identifies the multiple count problem which counts item ..."
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Abstract—COUNT is a typical aggregation operation in Wireless Sensor Networks (WSNs). In such an operation, the total number of the items which are of the same kind is obtained and only one numerical value is returned as the result. This paper identifies the multiple count problem which counts items
Approximating the Generalized Capacitated Treerouting Problem
"... In this paper, we introduce the generalized capacitated treerouting problem (GCTR), which is described as follows. Given a connected graph G = (V,E) with a sink s ∈ V and a set M ⊆ V − {s} of terminals with a nonnegative demand q(v), v ∈ M, we wish to find a collection T = {T1, T2,..., T`} of trees ..."
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In this paper, we introduce the generalized capacitated treerouting problem (GCTR), which is described as follows. Given a connected graph G = (V,E) with a sink s ∈ V and a set M ⊆ V − {s} of terminals with a nonnegative demand q(v), v ∈ M, we wish to find a collection T = {T1, T2,..., T`} of trees rooted at s to send all the demands to s, where the total demand collected by each tree Ti is bounded from above by a demand capacity κ> 0. Let λ> 0 denote a bulk capacity of an edge, and each edge e ∈ E has an installation cost w(e) ≥ 0 per bulk capacity; each edge e is allowed to have capacity kλ for any integer k, which installation incurs cost kw(e). To establish a tree routing Ti, each edge e contained in Ti requires α+βq ′ amount of capacity for the total demand q ′ that passes through edge e along Ti and prescribed constants α, β ≥ 0, where α means a fixed amount used to separate the inside of the routing Ti from the outside while term βq ′ means the net capacity proportional to q′. The objective of GCTR is to find a collection T of trees that minimizes the total installation cost of edges. Then GCTR is a new generalization of the several known multicast problems in networks with edge/demand capacities. In this paper, we prove that GCTR is (2[λ/(α + βκ)]/bλ/(α + βκ)c + ρST)approximable if λ ≥ α + βκ holds, where ρST is any approximation ratio achievable for the Steiner tree problem.
Predictionbased Routing with Packet Scheduling under Temporal Constraint in Delay Tolerant Networks
"... is a challenging problem due to the intermittent connectivity between the nodes. Researchers have proposed many routing protocols that adapt to the temporary connections of DTNs. One classification of routing protocols makes use of historical information to predict future contact patterns for any pa ..."
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is a challenging problem due to the intermittent connectivity between the nodes. Researchers have proposed many routing protocols that adapt to the temporary connections of DTNs. One classification of routing protocols makes use of historical information to predict future contact patterns for any pair of nodes. However, most existing protocols focus on the probability of a path from the source to the destination without considering the information in a packet which includes the source, destination, size, TTL (TimeToLive) and limited resources such as available buffer size and bandwidth. In this paper, we propose a new predictionbased routing algorithm that takes into account packet information under the conditions of limited transmission opportunities. The goal of this protocol is to increase the overall delivery ratio through scheduling packets at each node. Meanwhile, this protocol may sacrifice some messages ’ delivery delay time to some extent. Extensive simulation results with real traces show that our protocol with packet scheduling has better performance than the pure probabilistic routing algorithms in term of delivery ratio. Our protocol’s performance advantage is more obvious for nodes with higher packet intensity and shorter TTL in packets. I.
Article EnergyEfficient Algorithm for Multicasting in DutyCycled Sensor Networks
, 2015
"... Abstract: Multicasting is a fundamental network service for onetomany communications in wireless sensor networks. However, when the sensor nodes work in an asynchronous dutycycled way, the sender may need to transmit the same message several times to one group of its neighboring nodes, which comp ..."
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Abstract: Multicasting is a fundamental network service for onetomany communications in wireless sensor networks. However, when the sensor nodes work in an asynchronous dutycycled way, the sender may need to transmit the same message several times to one group of its neighboring nodes, which complicates the minimum energy multicasting problem. Thus, in this paper, we study the problem of minimum energy multicasting with adjusted power (the MEMAP problem) in the dutycycled sensor networks, and we prove it to be NPhard. To solve such a problem, the concept of an auxiliary graph is proposed to integrate the scheduling problem of the transmitting power and transmitting time slot and the constructing problem of the minimum multicast tree in MEMAP, and a greedy algorithm is proposed to construct such a graph. Based on the proposed auxiliary graph, an approximate scheduling and constructing algorithm with an approximation ratio of 4lnK is proposed, where K is the number of destination nodes. Finally, the theoretical analysis and experimental results verify the efficiency of the proposed algorithm in terms of the energy cost and transmission redundancy.
Data Aggregation Scheduling in Wireless Networks with Cognitive Radio Capability
"... Abstract—Complicated collisions and spectrum uncertainty constrain the usage of Cognitive Radio Networks (CRNs) on heavy transmission and time sensitive applications. On the other hand, data aggregation has been considered as an essential operation in wireless networks. A large amount of effort has ..."
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Abstract—Complicated collisions and spectrum uncertainty constrain the usage of Cognitive Radio Networks (CRNs) on heavy transmission and time sensitive applications. On the other hand, data aggregation has been considered as an essential operation in wireless networks. A large amount of effort has been dedicated to the investigation of CRNs and data aggregation in wireless networks. However, the existing literatures rarely concentrate on how to use cognitive radio technique to promote the performance of data aggregation in conventional wireless networks. In this paper, we investigate the Minimum Latency Data Aggregation Scheduling in wireless networks with Cognitive Radio capability (MLDASCR) problem. As the first try, an approximation scheduling algorithm based on Integer Linear Programming (ILP) and Linear Programming (LP) is proposed. According to the simulation results, this method performances great, however, it is difficult to theoretically evaluate the solution. Therefore, a heuristic scheduling algorithm with guaranteed latency bound is presented in our further investigation. The performance of the proposed solutions are evaluated through extensive simulations. I.