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18
W paths in wireless sensor networks
 Proceedings of MSN 2005
, 2005
"... All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately. ..."
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Cited by 19 (5 self)
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All intext references underlined in blue are linked to publications on ResearchGate, letting you access and read them immediately.
Data aggregation in sensor networks: Balancing communication and delay costs
 In Proc. of the 14th International Colloquium on Structural Information and Communication Complexity (SIROCCO 07), LNCS 4474
, 2007
"... Abstract. In a sensor network the sensors, or nodes, obtain data and have to communicate these data to a central node. Because sensors are battery powered they are highly energy constrained. Data aggregation can be used to combine data of several sensors into a single message, thus reducing sensor c ..."
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Abstract. In a sensor network the sensors, or nodes, obtain data and have to communicate these data to a central node. Because sensors are battery powered they are highly energy constrained. Data aggregation can be used to combine data of several sensors into a single message, thus reducing sensor communication costs at the expense of message delays. Thus, the main problem of data aggregation is to balance the communication and delay costs. In this paper we study the data aggregation problem as a bicriteria optimization problem; the objectives we consider are to minimize maximum energy consumption of a sensor and a function of the maximum latency costs of a message. We consider distributed algorithms under an asynchronous time model, and under an almost synchronous time model, where sensor clocks are synchronized up to a small drift. We use competitive analysis to assess the quality of the algorithms. Key words: distributed algorithms, sensor networks, data aggregation, bicriteria optimization. 1
Maximizing aggregated revenue in sensor networks under deadline constraints
 in CDC
, 2009
"... Abstract—We study the problem of maximizing the aggregated revenue in sensor networks with deadline constraints. Our model is that of a sensor network that is arranged in the form of a tree topology, where the root corresponds to the sink node, and the rest of the network detects an event and trans ..."
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Abstract—We study the problem of maximizing the aggregated revenue in sensor networks with deadline constraints. Our model is that of a sensor network that is arranged in the form of a tree topology, where the root corresponds to the sink node, and the rest of the network detects an event and transmits data to the sink over one or more hops. We assume a timeslotted synchronized system and a nodeexclusive (also called a primary) interference model. We formulate this problem as an integer optimization problem and show that the optimal solution involves solving a Bipartite Maximum Weighted Matching problem at each hop. We propose a polynomial time algorithm based on dynamic programming that uses only local information at each hop to obtain the optimal solution. Thus, we answer the question of when a node should stop waiting to aggregate data from its predecessors and start transmitting in order to maximize revenue within a deadline imposed by the sink. Further, we show that our optimization framework is general enough that it can be extended to a number of interesting cases such as incorporating sleepwake scheduling, minimizing aggregate sensing error, etc. I.
Tight Bounds for DelaySensitive Aggregation
, 2008
"... This paper studies the fundamental tradeoff between communication cost and delay cost arising in various contexts such as control message aggregation or organization theory. An optimization problem is considered where nodes are organized in a tree topology. The nodes seek to minimize the time until ..."
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Cited by 8 (1 self)
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This paper studies the fundamental tradeoff between communication cost and delay cost arising in various contexts such as control message aggregation or organization theory. An optimization problem is considered where nodes are organized in a tree topology. The nodes seek to minimize the time until the root is informed about their states and to use as few transmissions as possible at the same time. We derive an upper bound on the competitive ratio of O(min(h, c)) where h is the tree’s height, and c is the transmission cost per edge. Moreover, we prove that this upper bound is tight in the sense that any oblivious algorithm has a ratio of at least Ω(min(h, c)). For chain networks, we prove a tight competitive ratio of Θ(min ( √ h, c)). Furthermore, the paper introduces a new model for online event aggregation where the importance of an event depends on its difference to previous events.
Online function tracking with generalized penalties
 In Proc. 12th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT
, 2010
"... Abstract. We attend to the classic setting where an observer needs to inform a tracker about an arbitrary time varying function f : N0 → Z. This is an optimization problem, where both wrong values at the tracker and sending updates entail a certain cost. We consider an online variant of this proble ..."
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Cited by 7 (7 self)
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Abstract. We attend to the classic setting where an observer needs to inform a tracker about an arbitrary time varying function f : N0 → Z. This is an optimization problem, where both wrong values at the tracker and sending updates entail a certain cost. We consider an online variant of this problem, i.e., at time t, the observer only knows f (t ) for all t ≤ t. In this paper, we generalize existing cost models (with an emphasis on concave and convex penalties) and present two online algorithms. Our analysis shows that these algorithms perform well in a large class of models, and are even optimal in some settings.
When InNetwork Processing Meets Time: Complexity and Effects of Joint Optimization in Wireless Sensor Networks
"... Abstract—As sensornets are increasingly being deployed in missioncritical applications, it becomes imperative that we consider application QoS requirements in innetwork processing (INP). Towards understanding the complexity of joint QoS and INP optimization, we study the problem of jointly optimiz ..."
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Abstract—As sensornets are increasingly being deployed in missioncritical applications, it becomes imperative that we consider application QoS requirements in innetwork processing (INP). Towards understanding the complexity of joint QoS and INP optimization, we study the problem of jointly optimizing packet packing (i.e., aggregating shorter packets into longer ones) and the timeliness of data delivery. We identify the conditions under which the problem is strong NPhard, and we find that the problem complexity heavily depends on aggregation constraints (in particular, maximum packet size and reaggregation tolerance) instead of network and traffic properties. For cases when the problem is NPhard, we show that there is no polynomialtime approximation scheme (PTAS); for cases when the problem can be solved in polynomial time, we design polynomial time, offline algorithms for finding the optimal packet packing schemes. To understand the impact of joint QoS and INP optimization on sensornet performance, we design a distributed, online protocol tPack that schedules packet transmissions to maximize the local utility of packet packing at each node. Using a testbed of 130 TelosB motes, we experimentally evaluate the properties of tPack. We find that jointly optimizing data delivery timeliness and packet packing significantly improve network performance. Our findings shed light on the challenges, benefits, and solutions of joint QoS and INP optimization, and they also suggest open problems for future research. KeywordsWireless network, sensor network, realtime, packet packing, innetwork processing I.
EnergyEfficient Algorithms  Algorithmic solutions can help reduce energy consumption in computing environs
, 2010
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Scalable and Efficient Data Processing in Networked Control Systems Aida Ehyaei Scalable and Efficient Data Processing in Networked Control Systems © IPP Hurray! Research Group Scalable and Efficient Data Processing in Networked Control Systems
"... Abstract Network control systems (NCSs) are spatially distributed systems in which the communication between sensors, actuators and controllers occurs through a shared bandlimited digital communication network. However, the use of a shared communication network, in contrast to using several dedica ..."
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Abstract Network control systems (NCSs) are spatially distributed systems in which the communication between sensors, actuators and controllers occurs through a shared bandlimited digital communication network. However, the use of a shared communication network, in contrast to using several dedicated independent connections, introduces new challenges which are even more acute in large scale and dense networked control systems. In this paper we investigate a recently introduced technique of gathering information from a dense sensor network to be used in networked control applications. Obtaining efficiently an approximate interpolation of the sensed data is exploited as offering a good tradeoff between accuracy in the measurement of the input signals and the delay to the actuation. These are important aspects to take into account for the quality of control. We introduce a variation to the stateoftheart algorithms which we prove to perform relatively better because it takes into account the changes over time of the input signal within the process of obtaining an approximate interpolation.
A PTAS for Minimum Clique Partition in Unit Disk Graphs
, 2009
"... We consider the problem of partitioning the set of vertices of a given unit disk graph (UDG) into a minimum number of cliques. The problem is NPhard and various constant factor approximations are known, with the current best ratio of 3. Our main result is a polynomial time approximation scheme (PTA ..."
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We consider the problem of partitioning the set of vertices of a given unit disk graph (UDG) into a minimum number of cliques. The problem is NPhard and various constant factor approximations are known, with the current best ratio of 3. Our main result is a polynomial time approximation scheme (PTAS) for this problem on UDG. In fact, we present a robust algorithm that given a graph G (not necessarily UDG) with edgelengths, it either (i) computes a clique partition or (ii) gives a certificate that the graph is not a UDG; for the case (i) that it computes a clique partition, we show that it is guaranteed to be within (1+ε) ratio of the optimum if the input is UDG; however if the input is not a UDG it either computes a clique partition as in case (i) with no guarantee on the quality of the clique partition or detects that it is not a UDG. Noting that recognition of UDG’s is NPhard even if we are given edge lengths, our PTAS is a robust algorithm. Our main technical contribution involves showing the property of separability of an optimal clique partition; that there exists an optimal clique partition where the convex hulls of the cliques are pairwise nonoverlapping. Our algorithm can be transformed into an O log
Capacitated maxBatching with Interval Graph Compatibilities
, 2010
"... We consider the problem of partitioning interval graphs into cliques of bounded size. Each interval has a weight, and the cost of a clique is the maximum weight of any interval in the clique. This natural graph problem can be interpreted as a batch scheduling problem. Solving an open question from [ ..."
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We consider the problem of partitioning interval graphs into cliques of bounded size. Each interval has a weight, and the cost of a clique is the maximum weight of any interval in the clique. This natural graph problem can be interpreted as a batch scheduling problem. Solving an open question from [7, 4, 5], we show NPhardness, even if the bound on the clique sizes is constant. Moreover, we give a PTAS based on a novel dynamic programming technique for this case. 1