Results 1  10
of
67
AdHoc Networks Beyond Unit Disk Graphs
, 2003
"... In this paper we study a model for adhoc networks close enough to reality as to represent existing networks, being at the same time concise enough to promote strong theoretical results. The Quasi Unit Disk Graph model contains all edges shorter than a parameter d between 0 and 1 and no edges longer ..."
Abstract

Cited by 140 (11 self)
 Add to MetaCart
In this paper we study a model for adhoc networks close enough to reality as to represent existing networks, being at the same time concise enough to promote strong theoretical results. The Quasi Unit Disk Graph model contains all edges shorter than a parameter d between 0 and 1 and no edges longer than 1. We show that  in comparison to the cost known on Unit Disk Graphs  the complexity results in this model contain the additional factor 1/d&sup2;. We prove that in Quasi Unit Disk Graphs flooding is an asymptotically messageoptimal routing technique, provide a geometric routing algorithm being more efficient above all in dense networks, and show that classic geometric routing is possible with the same performance guarantees as for Unit Disk Graphs if d 1/ # 2.
The Complexity of Connectivity in Wireless Networks
 IN: PROC. OF THE 25 TH ANNUAL JOINT CONF. OF THE IEEE COMPUTER AND COMMUNICATIONS SOCIETIES (INFOCOM
, 2006
"... We define and study the scheduling complexity in wireless networks, which expresses the theoretically achievable efficiency of MAC layer protocols. Given a set of communication requests in arbitrary networks, the scheduling complexity describes the amount of time required to successfully schedule a ..."
Abstract

Cited by 115 (13 self)
 Add to MetaCart
We define and study the scheduling complexity in wireless networks, which expresses the theoretically achievable efficiency of MAC layer protocols. Given a set of communication requests in arbitrary networks, the scheduling complexity describes the amount of time required to successfully schedule all requests. The most basic and important network structure in wireless networks being connectivity, we study the scheduling complexity of connectivity, i.e., the minimal amount of time required until a connected structure can be scheduled. In this paper, we prove that the scheduling complexity of connectivity grows only polylogarithmically in the number of nodes. Specifically, we present a novel scheduling algorithm that successfully schedules a strongly connected set of links in time O(log 4 n) even in arbitrary worstcase networks. On the other hand, we prove that standard MAC layer or scheduling protocols can perform much worse. Particularly, any protocol that either employs uniform or linear (a node’s transmit power is proportional to the minimum power required to reach its intended receiver) power assignment has a Ω(n) scheduling complexity in the worst case, even for simple communication requests. In contrast, our polylogarithmic scheduling algorithm allows many concurrent transmission by using an explicitly formulated nonlinear power assignment scheme. Our results show that even in largescale worstcase networks, there is no theoretical scalability problem when it comes to scheduling transmission requests, thus giving an interesting complement to the more pessimistic bounds for the capacity in wireless networks. All results are based on the physical model of communication, which takes into account that the signaltonoise plus interference ratio (SINR) at a receiver must be above a certain threshold if the transmission is to be received correctly.
Improving spatial reuse through tuning transmit power, carrier sense threshold, and data rate in multihop wireless networks
 In Proc. of ACM MobiCom
, 2006
"... The importance of spatial reuse in wireless adhoc networks has been long recognized as a key to improving the network capacity. One can increase the level of spatial reuse by either reducing the transmit power or increasing the carrier sense threshold (thereby reducing the carrier sense range). On ..."
Abstract

Cited by 97 (6 self)
 Add to MetaCart
(Show Context)
The importance of spatial reuse in wireless adhoc networks has been long recognized as a key to improving the network capacity. One can increase the level of spatial reuse by either reducing the transmit power or increasing the carrier sense threshold (thereby reducing the carrier sense range). On the other hand, as the transmit power decreases or the carrier sense threshold increases, the SINR decreases as a result of the smaller received signal or the increased interference level. Consequently, the data rate sustained by each transmission may decrease. This leads naturally to the following questions: (1) How can the tradeoff between the increased level of spatial reuse and the decreased data rate each node can sustain be quantified? In other words, is there an optimal range of transmit power/carrier sense threshold in which the network capacity is maximized? (2) What is the relation between
FLSS: A FaultTolerant Topology Control Algorithm for Wireless Networks
, 2004
"... Topology control algorithms usually reduce the number of links in a wireless network, which in turn decreases the degree of connectivity. The resulting network topology is more susceptible to system faults such as node failures and departures. In this paper, we consider kvertex connectivity of a wi ..."
Abstract

Cited by 71 (4 self)
 Add to MetaCart
Topology control algorithms usually reduce the number of links in a wireless network, which in turn decreases the degree of connectivity. The resulting network topology is more susceptible to system faults such as node failures and departures. In this paper, we consider kvertex connectivity of a wireless network. We first present a centralized algorithm, Faulttolerant Global Spanning Subgraph (FGSSk), which preserves kvertex connectivity. FGSSk is minmax optimal, i.e., FGSSk minimizes the maximum transmission power used in the network, among all algorithms that preserve kvertex connectivity. Based on FGSSk, we propose a localized algorithm, Faulttolerant Local Spanning Subgraph (FLSSk). It is proved that FLSSk preserves kvertex connectivity while maintaining bidirectionality of the network, and FLSSk is minmax optimal among all strictly localized algorithms. We then relax several widely used assumptions for topology control to enhance the practicality of FGSSk and FLSSk. Simulation results show that FLSSk is more powerefficient than other existing distributed/localized topology control algorithms.
Localized topology control algorithms for heterogeneous wireless networks
 IEEE TRANS. ON NETWORKING
, 2005
"... Most existing topology control algorithms assume homogeneous wireless networks with uniform maximal transmission power, and cannot be directly applied to heterogeneous wireless networks where the maximal transmission power of each node may be different. We present two localized topology control alg ..."
Abstract

Cited by 30 (1 self)
 Add to MetaCart
Most existing topology control algorithms assume homogeneous wireless networks with uniform maximal transmission power, and cannot be directly applied to heterogeneous wireless networks where the maximal transmission power of each node may be different. We present two localized topology control algorithms for heterogeneous networks: Directed Relative Neighborhood Graph (DRNG) and Directed Local Spanning Subgraph (DLSS). In both algorithms, each node independently builds its neighbor set by adjusting the transmission power, and defines the network topology by using only local information. We prove that: 1) both DRNG and DLSS can preserve network connectivity; 2) the outdegree of any node in the resulting topology generated by DRNG or DLSS is bounded by a constant; and 3) DRNG and DLSS can preserve network bidirectionality. Simulation results indicate that DRNG and DLSS significantly outperform existing topology control algorithms for heterogeneous networks in several aspects.
The Capacity of Heterogeneous Wireless Networks
 Proc. IEEE INFOCOM
, 2010
"... Abstract—A substantial body of the literature exists addressing the capacity of wireless networks. However, it is commonly assumed that all nodes in the network are identical. The issue of heterogeneity has not been embraced into the discussions. In this paper, we investigate the throughput capacity ..."
Abstract

Cited by 14 (3 self)
 Add to MetaCart
(Show Context)
Abstract—A substantial body of the literature exists addressing the capacity of wireless networks. However, it is commonly assumed that all nodes in the network are identical. The issue of heterogeneity has not been embraced into the discussions. In this paper, we investigate the throughput capacity of heterogeneous wireless networks with general network settings. Specifically, we consider an extended network with n normal nodes and m nb (0 b 1) more powerful helping nodes in a rectangular area with width sðnÞ and length n=sðnÞ, where sðnÞ nw and 0 w 1=2. We assume that there are n flows in the network. All the n normal nodes are sources while only randomly chosen nd (0 d 1) normal nodes are destinations. We further assume that the n normal nodes are uniformly and independently distributed, while the m helping nodes are either regularly placed or uniformly and independently distributed, resulting in two different kinds of networks called Regular Heterogeneous Wireless Networks and Random Heterogeneous Wireless Networks, respectively. We show that network capacity is determined by the shape of the network area, the number of destination nodes, the number of helping nodes, and the bandwidth of helping nodes. We also find that heterogeneous wireless networks can provide throughput higher in the order sense than traditional homogeneous wireless networks only under certain conditions. Index Terms—Heterogeneous wireless networks, extended networks, achievable throughput Ç 1
Proximity Structures for Geometric Graphs
 International Journal of Computational Geometry and Applications
, 2003
"... In this paper we study proximity structures like Delaunay triangulations based on geometric graphs, i.e. graphs which are subgraphs of the complete geometric graph. Given an arbitrary geometric graph G, we define several restricted Voronoi diagrams, restricted Delaunay triangulations, relative n ..."
Abstract

Cited by 12 (0 self)
 Add to MetaCart
In this paper we study proximity structures like Delaunay triangulations based on geometric graphs, i.e. graphs which are subgraphs of the complete geometric graph. Given an arbitrary geometric graph G, we define several restricted Voronoi diagrams, restricted Delaunay triangulations, relative neighborhood graphs, Gabriel graphs and then study their complexities when G is a general geometric graph or G is some special graph derived from the application area of wireless networks. Besides being of fundamental interest these structures have applications in topology control for wireless networks.
Localized Movement Control for Fault Tolerance of Mobile Robot Networks
 in Proceedings of The First IFIP International Conference on Wireless Sensor and Actor Networks (WSAN 2007
, 2007
"... Abstract. In this paper, we present a novel localized movement control algorithm to form a faulttolerant biconnected robotic network topology from a connected network, such that total distance of movement of robots is minimized. The proposed distributed algorithm uses phop neighbor information t ..."
Abstract

Cited by 11 (3 self)
 Add to MetaCart
(Show Context)
Abstract. In this paper, we present a novel localized movement control algorithm to form a faulttolerant biconnected robotic network topology from a connected network, such that total distance of movement of robots is minimized. The proposed distributed algorithm uses phop neighbor information to identify critical head robots that can direct two neighbors to move toward each other and biconnect their neighborhood. Simulation results show that the total distance of movement of robots decreases significantly with our localized algorithm when compared to the globalized one, and our localized algorithm achieved 100 % success on considered nonbiconnected networks. To the best of our knowledge, it is the first work on localized movement control for fault tolerance of mobile robot networks.
Relay deployment and power control for lifetime elongation in sensor networks
 in IEEE ICC
, 2006
"... Abstract — In a sensor network, usually a large number of sensors transport data messages to a limited number of sinks. Due to this multipointtopoint communications pattern in general homogeneous sensor networks, the closer a sensor to the sink, the quicker it will deplete its battery. This unbala ..."
Abstract

Cited by 8 (4 self)
 Add to MetaCart
Abstract — In a sensor network, usually a large number of sensors transport data messages to a limited number of sinks. Due to this multipointtopoint communications pattern in general homogeneous sensor networks, the closer a sensor to the sink, the quicker it will deplete its battery. This unbalanced energy depletion phenomenon has become the bottleneck problem to elongate the lifetime of sensor networks. In this paper, we consider the effects of joint relay node deployment and transmission power control on network lifetime. Contrary to the intuition the relay nodes considered are even simpler devices than the sensor nodes with limited capabilities. We show that the network lifetime can be extended significantly with the addition of relay nodes to the network. In addition, for the same expected network lifetime goal, the number of relay nodes required can be reduced by employing efficient transmission power control while leaving the network connectivity level unchanged. The solution suggests that it is sufficient to deploy relay nodes only with a specific probabilistic distribution rather than the specifying the exact places. Furthermore, the solution does not require any change on the protocols (such as routing) used in the network. I.
Towards an optimal positioning of multiple mobile sinks in wsns for buildings
 Int J On Advances in Intelligent Systems
"... The need for wireless sensor networks is rapidly growing in a wide range of applications specially for buildings automation. In such networks, a large number of sensors with limited energy supply are in charge of relaying the sensed data hop by hop to the nearest sink. The sensors closest to the sin ..."
Abstract

Cited by 8 (4 self)
 Add to MetaCart
(Show Context)
The need for wireless sensor networks is rapidly growing in a wide range of applications specially for buildings automation. In such networks, a large number of sensors with limited energy supply are in charge of relaying the sensed data hop by hop to the nearest sink. The sensors closest to the sinks deplete their energy much faster than distant nodes because they carry heavy traffic which causes prematurely the end of the network lifetime. Employing mobile sinks can alleviate this problem by distributing the high traffic load among the sensors and increase the network lifetime. In this work, we aim to find the best way to relocate sinks inside buildings by determining their optimal locations and the duration of their sojourn time. Therefore, we propose an Integer Linear Program for multiple mobile sinks which directly maximizes the network lifetime instead of minimizing the energy consumption or maximizing the residual energy, which is what was done in previous solutions. We evaluated the performance of our approach by simulation and compared it with others schemes. The results show that our solution extends significantly the network lifetime and balances notably the energy consumption among the nodes.