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103
Routing in a delay tolerant network
 Proceedings of ACM Sigcomm
, 2004
"... We formulate the delaytolerant networking routing problem, where messages are to be moved endtoend across a connectivity graph that is timevarying but whose dynamics may be known in advance. The problem has the added constraints of finite buffers at each node and the general property that no con ..."
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Cited by 464 (6 self)
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We formulate the delaytolerant networking routing problem, where messages are to be moved endtoend across a connectivity graph that is timevarying but whose dynamics may be known in advance. The problem has the added constraints of finite buffers at each node and the general property that no contemporaneous endtoend path may ever exist. This situation limits the applicability of traditional routing approaches that tend to treat outages as failures and seek to find an existing endtoend path. We propose a framework for evaluating routing algorithms in such environments. We then develop several algorithms and use simulations to compare their performance with respect to the amount of knowledge they require about network topology. We find that, as expected, the algorithms using the least knowledge tend to perform poorly. We also find that with limited additional knowledge, far less than complete global knowledge, efficient algorithms can be constructed for routing in such environments. To the best of our knowledge this is the first such investigation of routing issues in DTNs.
Dynamic Server Allocation to Parallel Queues with Randomly Varying Connectivity
 IEEE Transactions on Information Theory
, 1993
"... this paper, we consider a queueing model of a singlehop network with randomly changing connectivity and we study the effect of varying connectivity on the performance of the system. The queueing model consists of a single server and N parallel queues (Fig. 1). The time is slotted. At slot t each qu ..."
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Cited by 198 (1 self)
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this paper, we consider a queueing model of a singlehop network with randomly changing connectivity and we study the effect of varying connectivity on the performance of the system. The queueing model consists of a single server and N parallel queues (Fig. 1). The time is slotted. At slot t each queue i may be either connected to the server or not; that is denoted by the binary variable Ci(t), which is equal to 1 and 0 respectively. It is called the connectivity variable of queue i. The connectivity varies randomly with time. There are Manuscript received August 20, 1991; revised February 24, 1992. This work was presented in part at the IEEE International Symposium on Information Theory, Budapest, Hungary, June 2428, 1991. L. Tassiulas is with the Department of Electrical Engineering, Polytechnic University, 6 Metrotech Center, Brooklyn, NY 11201. A. Ephremides is with the Department of Electrical Engineering, University of Maryland, College Park, MD 20742. IEEE Log Number 9204101. cffO ........ a I a 2 Fig. 1. Singlehop network with time varying connectivity. Solid line between a queue and the server denotes that the queue is connected to the server (it may receive service). Dashed line denotes that the queue is disconnected
Shortest Path Algorithms in Transportation Models: Classical and Innovative Aspects
, 1998
"... Shortest Path Problems are among the most studied network flow optimization problems, with interesting applications in various fields. One such field is transportation, where shortest path problems of different kinds need to be solved. Due to the nature of the application, transportation scientists ..."
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Cited by 54 (3 self)
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Shortest Path Problems are among the most studied network flow optimization problems, with interesting applications in various fields. One such field is transportation, where shortest path problems of different kinds need to be solved. Due to the nature of the application, transportation scientists need very flexible and efficient shortest path procedures, both from the running time point of view, and also for the memory requirements. Since no "best" algorithm currently exists for every kind of transportation problem, research in this field has recently moved to the design and implementation of "ad hoc" shortest path procedures, which are able to capture the peculiarities of the problems under consideration. The aim of this work is to present in a unifying framework both the main algorithmic approaches that have been proposed in the past years for solving the shortest path problems arising most frequently in the transportation field, and also some important implementation techniques ...
The diameter of opportunistic mobile networks
, 2007
"... Portable devices have more data storage and increasing communication capabilities everyday. In addition to classic infrastructure based communication, these devices can exploit human mobility and opportunistic contacts to communicate. We analyze the characteristics of such opportunistic forwarding p ..."
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Cited by 43 (8 self)
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Portable devices have more data storage and increasing communication capabilities everyday. In addition to classic infrastructure based communication, these devices can exploit human mobility and opportunistic contacts to communicate. We analyze the characteristics of such opportunistic forwarding paths. We establish that opportunistic mobile networks in general are characterized by a small diameter, a destination device is reachable using only a small number of relays under tight delay constraint. This property is first demonstrated analytically on a family of mobile networks which follow a random graph process. We then establish the validity of this result empirically with four data sets capturing human mobility, using a new methodology to efficiently compute all the paths that impact the diameter of an opportunistic mobile networks. We complete our analysis of network diameter by studying the impact of intensity of contact rate and contact duration. This work is, to our knowledge, the first validation that the so called “small world ” phenomenon applies very generally to opportunistic networking between mobile nodes. 1.
TDrive: Driving directions based on taxi trajectories
 ACM SIGSPATIAL GIS
, 2010
"... GPSequipped taxis can be regarded as mobile sensors probing traffic flows on road surfaces, and taxi drivers are usually experienced in finding the fastest (quickest) route to a destination based on their knowledge. In this paper, we mine smart driving directions from the historical GPS trajectorie ..."
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Cited by 39 (13 self)
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GPSequipped taxis can be regarded as mobile sensors probing traffic flows on road surfaces, and taxi drivers are usually experienced in finding the fastest (quickest) route to a destination based on their knowledge. In this paper, we mine smart driving directions from the historical GPS trajectories of a large number of taxis, and provide a user with the practically fastest route to a given destination at a given departure time. In our approach, we propose a timedependent landmark graph, where a node (landmark) is a road segment frequently traversed by taxis, to model the intelligence of taxi drivers and the properties of dynamic road networks. Then, a VarianceEntropyBased Clustering approach is devised to estimate the distribution of travel time between two landmarks in different time slots. Based on this graph, we design a twostage routing algorithm to compute the practically fastest route. We build our system based on a realworld trajectory dataset generated by over 33,000 taxis in a period of 3 months, and evaluate the system by conducting both synthetic experiments and inthefield evaluations. As a result, 60–70 % of the routes suggested by our method are faster than the competing methods, and 20 % of the routes share the same results. On average, 50 % of our routes are at least 20 % faster than the competing approaches.
MINIMUM WEIGHT PATHS in TIMEDEPENDENT NETWORKS
 NETWORKS
, 1991
"... We investigate the minimum weight path problem in networks whose link weights and link delays are both functions of time. We demonstrate that in general there exist cases in which no finite path is optimal leading us to define an infinite path (naturally, containing loops) in such a way that the min ..."
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Cited by 33 (3 self)
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We investigate the minimum weight path problem in networks whose link weights and link delays are both functions of time. We demonstrate that in general there exist cases in which no finite path is optimal leading us to define an infinite path (naturally, containing loops) in such a way that the minimum weight problem always has a solution. We also characterize the structure of an infinite optimal path. In many practical cases, finite optimal paths do exist. We formulate a criterion that guarantees the existence of a finite optimal path and develop an algorithm to find such a path. Some special cases, e.g., optimal loopless paths, are also discussed.
Engineering Route Planning Algorithms
 ALGORITHMICS OF LARGE AND COMPLEX NETWORKS. LECTURE NOTES IN COMPUTER SCIENCE
, 2009
"... Algorithms for route planning in transportation networks have recently undergone a rapid development, leading to methods that are up to three million times faster than Dijkstra’s algorithm. We give an overview of the techniques enabling this development and point out frontiers of ongoing research on ..."
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Cited by 30 (18 self)
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Algorithms for route planning in transportation networks have recently undergone a rapid development, leading to methods that are up to three million times faster than Dijkstra’s algorithm. We give an overview of the techniques enabling this development and point out frontiers of ongoing research on more challenging variants of the problem that include dynamically changing networks, timedependent routing, and flexible objective functions.
Efficient Models for Timetable Information in Public Transportation Systems
 ACM JOURNAL OF EXPERIMENTAL ALGORITHMICS
, 2008
"... We consider two approaches that model timetable information in public transportation systems as shortestpath problems in weighted graphs. In the timeexpanded approach, every event at a station, e.g., the departure of a train, is modeled as a node in the graph, while in the timedependent approach t ..."
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Cited by 28 (10 self)
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We consider two approaches that model timetable information in public transportation systems as shortestpath problems in weighted graphs. In the timeexpanded approach, every event at a station, e.g., the departure of a train, is modeled as a node in the graph, while in the timedependent approach the graph contains only one node per station. Both approaches have been recently considered for (a simplified version of) the earliest arrival problem, but little is known about their relative performance. Thus far, there are only theoretical arguments in favor of the timedependent approach. In this paper, we provide the first extensive experimental comparison of the two approaches. Using several realworld data sets, we evaluate the performance of the basic models and of several new extensions towards realistic modeling. Furthermore, new insights on solving bicriteria optimization problems in both models are presented. The timeexpanded approach turns out to be more robust for modeling more complex scenarios, whereas the timedependent approach shows a clearly better performance.
Finding timedependent shortest paths over large graphs
 In Proc. EDBT
, 2008
"... The spatial and temporal databases have been studied widely and intensively over years. In this paper, we study how to answer queries of finding the best departure time that minimizes the total travel time from a place to another, over a road network, where the traffic conditions dynamically change ..."
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Cited by 24 (1 self)
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The spatial and temporal databases have been studied widely and intensively over years. In this paper, we study how to answer queries of finding the best departure time that minimizes the total travel time from a place to another, over a road network, where the traffic conditions dynamically change from time to time. We study a generalized form of this problem, called the timedependent shortestpath problem. A timedependent graph GT is a graph that has an edgedelay function, wi,j(t), associated with each edge (vi, vj), to be stored in a database. The edgedelay function wi,j(t) specifies how much time it takes to travel from node vi to node vj, if it departs from vi at time t. A userspecified query is to ask the minimumtraveltime path, from a source node, vs, to a destination node, ve, over the timedependent graph, GT, with the best departure time to be selected from a time interval T. We denote this user query as LTT(vs, ve, T) over GT. The challenge of this problem is the added complexity due to the time dependency in the timedependent graph. That is, edge delays are not constants, and can vary from time to time. In this paper, we propose a novel algorithm to find the minimumtraveltime path with the best departure time for a LTT(vs, ve, T) query over a large graph GT. Our approach outperforms existing algorithms in terms of both time complexity in theory and efficiency in practice. We will discuss the design of our algorithm, together with its correctness and complexity. We conducted extensive experimental studies over large graphs and will report our findings. 1.
Finding fastest paths on a road network with speed patterns
 In Proc. Int. Conf. on Data Engineering (ICDE’06
, 2006
"... This paper proposes and solves the TimeInterval All Fastest Path (allFP) query. Given a userdefined leaving or arrival time interval I, a source node s and an end node e, allFP asks for a set of all fastest paths from s to e, one for each subinterval of I. Note that the query algorithm should fin ..."
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Cited by 21 (0 self)
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This paper proposes and solves the TimeInterval All Fastest Path (allFP) query. Given a userdefined leaving or arrival time interval I, a source node s and an end node e, allFP asks for a set of all fastest paths from s to e, one for each subinterval of I. Note that the query algorithm should find a partitioning of I into subintervals. Existing methods can only be used to solve a very special case of the problem, when the leaving time is a single time instant. A straightforward solution to the allFP query is to run existing methods many times, once for every time instant in I. This paper proposes a solution based on novel extensions to the A * algorithm. Instead of expanding the network many times, we expand once. The travel time on a path is kept as a function of leaving time. Methods to combine traveltime functions are provided to expand a path. A novel lowerbound estimator for travel time is proposed. Performance results reveal that our method is more efficient and more accurate than the discretetime approach. 1