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62
Mobile Element Scheduling for Efficient Data Collection in Wireless Sensor Networks with Dynamic Deadlines
 In IEEE RTSS
, 2004
"... Wireless networks have historically considered support for mobile elements as an extra overhead. However, recent research has provided means by which network can take advantage of mobile elements. Particularly, in the case of wireless sensor networks, mobile elements are deliberately built into the ..."
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Cited by 97 (3 self)
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Wireless networks have historically considered support for mobile elements as an extra overhead. However, recent research has provided means by which network can take advantage of mobile elements. Particularly, in the case of wireless sensor networks, mobile elements are deliberately built into the system to improve the lifetime of the network, and act as mechanical carriers of data. The mobile element, which is controlled, visits the nodes to collect their data before their buffers are full. It may happen that the sensor nodes are sampling at different rates, in which case some nodes need to be visited more frequently than others. We present this problem of scheduling the mobile element in the network, so that there is no data loss due to buffer overflow. We prove that the problem is NPComplete and give an ILP formulation. We give some practical algorithms, and compare their performances.
Approximation Algorithms for Orienteering and DiscountedReward TSP
, 2003
"... In this paper, we give the first constantfactor approximation algorithm for the rooted Orienteering problem, as well as a new problem that we call the DiscountedReward TSP, motivated by robot navigation. In both problems, we are given a graph with lengths on edges and prizes (rewards) on nodes, ..."
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Cited by 81 (1 self)
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In this paper, we give the first constantfactor approximation algorithm for the rooted Orienteering problem, as well as a new problem that we call the DiscountedReward TSP, motivated by robot navigation. In both problems, we are given a graph with lengths on edges and prizes (rewards) on nodes, and a start node s. In the Orienteering Problem, the goal is to find a path that maximizes the reward collected, subject to a hard limit on the total length of the path. In the DiscountedReward TSP, instead of a length limit we are given a discount factor fl, and the goal is to maximize total discounted reward collected, where reward for a node reached at time t is discounted by fl . This is similar to the objective considered in Markov Decision Processes (MDPs) except we only receive a reward the first time a node is visited. We also consider tree and multiplepath variants of these problems and provide approximations for those as well. Although the unrooted orienteering problem, where there is no fixed start node s, has been known to be approximable using algorithms for related problems such as kTSP (in which the amount of reward to be collected is fixed and the total length is approximately minimized), ours is the first to approximate the rooted question, solving an open problem of [3, 1].
Combination Can Be Hard: Approximability of the Unique Coverage Problem
 In Proceedings of the 17th Annual ACMSIAM Symposium on Discrete Algorithms
, 2006
"... Abstract We prove semilogarithmic inapproximability for a maximization problem called unique coverage:given a collection of sets, find a subcollection that maximizes the number of elements covered exactly once. Specifically, assuming that NP 6 ` BPTIME(2n " ) for an arbitrary "> ..."
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Cited by 79 (2 self)
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Abstract We prove semilogarithmic inapproximability for a maximization problem called unique coverage:given a collection of sets, find a subcollection that maximizes the number of elements covered exactly once. Specifically, assuming that NP 6 ` BPTIME(2n &quot; ) for an arbitrary &quot;> 0, we prove O(1 / logoe n) inapproximability for some constant oe = oe(&quot;). We also prove O(1 / log1/3 &quot; n) inapproximability, forany &quot;> 0, assuming that refuting random instances of 3SAT is hard on average; and prove O(1 / log n)inapproximability under a plausible hypothesis concerning the hardness of another problem, balanced bipartite independent set. We establish an \Omega (1 / log n)approximation algorithm, even for a moregeneral (budgeted) setting, and obtain an \Omega (1 / log B)approximation algorithm when every set hasat most B elements. We also show that our inapproximability results extend to envyfree pricing, animportant problem in computational economics. We describe how the (budgeted) unique coverage problem, motivated by realworld applications, has close connections to other theoretical problemsincluding max cut, maximum coverage, and radio broadcasting. 1 Introduction In this paper we consider the approximability of the following natural maximization analog of set cover: Unique Coverage Problem. Given a universe U = {e1,..., en} of elements, and given a collection S = {S1,..., Sm} of subsets of U. Find a subcollection S0 ` S to maximize the number of elements that are uniquely covered, i.e., appear in exactly one set of S 0.
Maximum coverage problem with group budget constraints and applications
 PROC. OF APPROX, SPRINGER LNCS, 72–83
, 2004
"... We study a variant of the maximum coverage problem which we label the maximum coverage problem with group budget constraints (MCG). We are given a collection of sets S = {S1, S2,..., Sm} where each set Si is a subset of a given ground set X. In the maximum coverage problem the goal is to pick k set ..."
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Cited by 58 (4 self)
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We study a variant of the maximum coverage problem which we label the maximum coverage problem with group budget constraints (MCG). We are given a collection of sets S = {S1, S2,..., Sm} where each set Si is a subset of a given ground set X. In the maximum coverage problem the goal is to pick k sets from S to maximize the cardinality of their union. In the MCG problem S is partitioned into groups G1, G2,..., Gℓ. The goal is to pick k sets from S to maximize the cardinality of their union but with the additional restriction that at most one set be picked from each group. We motivate the study of MCG by pointing out a variety of applications. We show that the greedy algorithm gives a 2approximation algorithm for this problem which is tight in the oracle model. We also obtain a constant factor approximation algorithm for the cost version of the problem. We then use MCG to obtain the first constant factor approximation algorithms for the following problems: (i) multiple depot ktraveling repairmen problem with covering constraints and (ii) orienteering problem with time windows when the number of time windows is a constant.
A Recursive Greedy Algorithm for Walks in Directed Graphs
 PROC. OF IEEE FOCS
, 2005
"... Given an arcweighted directed graph G = (V, A, ℓ) and a pair of nodes s, t, we seek to find an st walk of length at most B that maximizes some given function f of the set of nodes visited by the walk. The simplest case is when we seek to maximize the number of nodes visited: this is called the ori ..."
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Cited by 52 (3 self)
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Given an arcweighted directed graph G = (V, A, ℓ) and a pair of nodes s, t, we seek to find an st walk of length at most B that maximizes some given function f of the set of nodes visited by the walk. The simplest case is when we seek to maximize the number of nodes visited: this is called the orienteering problem. Our main result is a quasipolynomial time algorithm that yields an O(log OPT) approximation for this problem when f is a given submodular set function. We then extend it to the case when a node v is counted as visited only if the walk reaches v in its time window [R(v), D(v)]. We apply the algorithm to obtain several new results. First, we obtain an O(log OPT) approximation for a generalization of the orienteering problem in which the profit for visiting each node may vary arbitrarily with time. This captures the time window problem considered earlier for which, even in undirected graphs, the best approximation ratio known [4] is O(log 2 OPT). The second application is an O(log 2 k) approximation for the kTSP problem in directed graphs (satisfying asymmetric triangle inequality). This is the first nontrivial approximation algorithm for this problem. The third application is an O(log 2 k) approximation (in quasipoly time) for the group Steiner problem in undirected graphs where k is the number of groups. This improves earlier ratios [15, 19, 8] by a logarithmic factor and almost matches the inapproximability threshold on trees [20]. This connection to group Steiner trees also enables us to prove that the problem we consider is hard to approximate to a ratio better than Ω(log 1−ɛ OPT), even in undirected graphs. Even though our algorithm runs in quasipoly time, we believe that the implications for the approximability of several basic optimization problems are interesting.
Improved Algorithms for Orienteering and Related Problems
, 2007
"... In this paper we consider the orienteering problem in undirected and directed graphs and obtain improved approximation algorithms. The point to pointorienteeringproblem is the following: Given an edgeweighted graph G = (V, E) (directed or undirected), two nodes s, t ∈ V and a budget B, find an st ..."
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Cited by 50 (6 self)
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In this paper we consider the orienteering problem in undirected and directed graphs and obtain improved approximation algorithms. The point to pointorienteeringproblem is the following: Given an edgeweighted graph G = (V, E) (directed or undirected), two nodes s, t ∈ V and a budget B, find an st walk in G of total length at most B that maximizes the number of distinct nodes visited by the walk. This problem is closely related to tour problems such as TSP as well as network design problems such as kMST. Our main results are the following. • A 2 + ɛ approximation in undirected graphs, improving upon the 3approximation from [5]. • An O(log 2 OPT) approximation in directed graphs. Previously, only a quasipolynomial time algorithm achieved a polylogarithmic approximation [12] (a ratio of O(log OPT)). The above results are based on, or lead to, improved algorithms for several other related problems.
On trip planning queries in spatial databases
 In SSTD
, 2005
"... In this paper we discuss a new type of query in Spatial Databases, called the Trip Planning Query (TPQ). Given a set of points of interest P in space, where each point belongs to a specific category, a starting point S and a destination E, TPQ retrieves the best trip that starts at S, passes through ..."
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Cited by 40 (1 self)
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In this paper we discuss a new type of query in Spatial Databases, called the Trip Planning Query (TPQ). Given a set of points of interest P in space, where each point belongs to a specific category, a starting point S and a destination E, TPQ retrieves the best trip that starts at S, passes through at least one point from each category, and ends at E. For example, a driver traveling from Boston to Providence might want to stop to a gas station, a bank and a post office on his way, and the goal is to provide him with the best possible route (in terms of distance, traffic, road conditions, etc.). The difficulty of this query lies in the existence of multiple choices per category. In this paper, we study fast approximation algorithms for TPQ in a metric space. We provide a number of approximation algorithms with approximation ratios that depend on either the number of categories, the maximum number of points
Partitioning based mobile element scheduling in wireless sensor networks
 IN. PROC. SECOND ANNUAL IEEE CONFERENCE ON SENSOR AND AD HOC COMMUNICATIONS AND NETWORKS (SECON
, 2005
"... In recent studies, using mobile elements (MEs) as mechanical carriers of data has been shown to be an effective way of prolonging sensor network life time and relaying information in partitioned networks. As the data generation rates of sensors may vary, some sensors need to be visited more frequent ..."
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Cited by 33 (0 self)
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In recent studies, using mobile elements (MEs) as mechanical carriers of data has been shown to be an effective way of prolonging sensor network life time and relaying information in partitioned networks. As the data generation rates of sensors may vary, some sensors need to be visited more frequently than others. In this paper, a partitioningbased algorithm is presented that schedules the movements of MEs in a sensor network such that there is no data loss due to buffer overflow. Simulation results show that the proposed Partitioning Based Scheduling (PBS) algorithm performs well in terms of reducing the minimum required ME speed to prevent data loss, providing high predictability in intervisit durations, and minimizing the data loss rate for the cases when the ME is constrained to move slower than the minimum required ME speed.
A Survey on Topology Control
 in Wireless Sensor Networks: Taxonomy, Comparative Study, and Open Issues. Proceedings of the IEEE
, 2013
"... A newly designed Ag/Ag+ reference electrode in a quartz tube with a tungsten tip junction (WtipQuartz REF) was fabricated and its electrochemical performance was compared with a conventional Pyrex tubebased Ag/Ag+ reference electrode (PyREF). The results of the electrochemical potential measure ..."
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Cited by 28 (3 self)
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A newly designed Ag/Ag+ reference electrode in a quartz tube with a tungsten tip junction (WtipQuartz REF) was fabricated and its electrochemical performance was compared with a conventional Pyrex tubebased Ag/Ag+ reference electrode (PyREF). The results of the electrochemical potential measurements with the WtipQuartzREF and the PyREF in the LiClKCl eutectic melts for a wide temperature range proved that the oxide layer on the surface of the tungsten metal tip provided a high ionic conduction. Stability of our newly designed WtipQuartzREF was tested by measuring a junction potential for 12 hours at 700oC. The results of the cyclic voltammetric measurement indicated that the Ag/Ag+ reference electrode in the quartz tube with a tungsten tip junction can provide a good performance for a wide temperature range.
Automatic Construction of Travel Itineraries using Social Breadcrumbs
"... Vacation planning is one of the frequent—but nonetheless laborious—tasks that people engage themselves with online; requiring skilled interaction with a multitude of resources. This paper constructs intracity travel itineraries automatically by tapping a latent source reflecting geotemporal breadc ..."
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Cited by 21 (0 self)
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Vacation planning is one of the frequent—but nonetheless laborious—tasks that people engage themselves with online; requiring skilled interaction with a multitude of resources. This paper constructs intracity travel itineraries automatically by tapping a latent source reflecting geotemporal breadcrumbs left by millions of tourists. For example, the popular rich media sharing site, Flickr, allows photos to be stamped by the time of when they were taken and be mapped to Points Of Interests (POIs) by geographical (i.e. latitudelongitude) and semantic (e.g., tags) metadata. Leveraging this information, we construct itineraries following a twostep approach. Given a city, we first extract photo streams of individual users. Each photo stream provides estimates on where the user was, how long he stayed at each place, and what was the transit time between places. In the second step, we aggregate all user photo streams into a POI graph. Itineraries are then automatically constructed from the graph based on the popularity of the POIs and subject to the user’s time and destination constraints. We evaluate our approach by constructing itineraries for several major cities and comparing them, through a“crowdsourcing” marketplace (Amazon Mechanical Turk), against itineraries constructed from popular bus tours that are professionally generated. Our extensive surveybased user studies over about 450 workers on AMT indicate that high quality itineraries can be automatically constructed from Flickr data.