Results 1  10
of
151
Dynamic Power Allocation and Routing for Time Varying Wireless Networks
 IEEE Journal on Selected Areas in Communications
, 2003
"... We consider dynamic routing and power allocation for a wireless network with time varying channels. The network consists of power constrained nodes which transmit over wireless links with adaptive transmission rates. Packets randomly enter the system at each node and wait in output queues to be tran ..."
Abstract

Cited by 358 (73 self)
 Add to MetaCart
We consider dynamic routing and power allocation for a wireless network with time varying channels. The network consists of power constrained nodes which transmit over wireless links with adaptive transmission rates. Packets randomly enter the system at each node and wait in output queues to be transmitted through the network to their destinations. We establish the capacity region of all rate matrices (# ij ) that the system can stably supportwhere (# ij ) represents the rate of traffic originating at node i and destined for node j. A joint routing and power allocation policy is developed which stabilizes the system and provides bounded average delay guarantees whenever the input rates are within this capacity region. Such performance holds for general arrival and channel state processes, even if these processes are unknown to the network controller. We then apply this control algorithm to an adhoc wireless network where channel variations are due to user mobility, and compare its performance with the GrossglauserTse relay model developed in [13].
Coverage in Wireless Adhoc Sensor Networks
, 2002
"... Sensor networks pose a number of challenging conceptual and optimization problems such as location, deployment, and tracking [1]. One of the fundamental problems in sensor networks is the calculation of the coverage. In [1], it is assumed that the sensor has the uniform sensing ability. In this pape ..."
Abstract

Cited by 162 (11 self)
 Add to MetaCart
(Show Context)
Sensor networks pose a number of challenging conceptual and optimization problems such as location, deployment, and tracking [1]. One of the fundamental problems in sensor networks is the calculation of the coverage. In [1], it is assumed that the sensor has the uniform sensing ability. In this paper, we give efficient distributed algorithms to optimally solve the bestcoverage problem raised in [1]. Here, we consider the sensing model: the sensing ability diminishes as the distance increases. As energy conservation is a major concern in wireless (or sensor) networks, we also consider how to find an optimum bestcoverage path with the least energy consumption. We also consider how to find an optimum bestcoveragepath that travels a small distance. In addition, we justify the correctness of the method proposed in [1] that uses the Delaunay triangulation to solve the best coverage problem. Moreover, we show that the search space of the best coverage problem can be confined to the relative neighborhood graph, which can be constructed locally.
The Critical Transmitting Range for Connectivity in Sparse Wireless Ad Hoc Networks
, 2003
"... In this paper, we analyze the critical transmitting range for connectivity in wireless ad hoc networks. More specifically, we consider the following problem: assume n nodes, each capable of communicating with nodes within a radius of r, are randomly and uniformly distributed in a ddimensional re ..."
Abstract

Cited by 149 (12 self)
 Add to MetaCart
(Show Context)
In this paper, we analyze the critical transmitting range for connectivity in wireless ad hoc networks. More specifically, we consider the following problem: assume n nodes, each capable of communicating with nodes within a radius of r, are randomly and uniformly distributed in a ddimensional region with a side of length l; how large must the transmitting range r be to ensure that the resulting network is connected with high probability? First, we consider this problem for stationary networks, and we provide tight upper and lower bounds on the critical transmitting range for onedimensional networks, and nontight bounds for two and threedimensional networks. Due to the presence of the geometric parameter l in the model, our results can be applied to dense as well as sparse ad hoc networks, contrary to existing theoretical results that apply only to dense networks. We also investigate several related questions through extensive simulations. First, we evaluate the relationship between the critical transmitting range and the minimum transmitting range that ensures formation of a connected component containing a large fraction (e.g. 90%) of the nodes. Then, we consider the mobile version of the
Computationally Efficient Scheduling with the Physical Interference Model for Throughput Improvement in Wireless Mesh Networks
 in Wireless Mesh Networks,” in Proc. ACM MobiCom
, 2006
"... Wireless mesh networks are expected to be widely used to provide Internet access in the near future. In order to fulfill the expectations, these networks should provide high throughput simultaneously to many users. Recent research has indicated that, due to its conservative CSMA/CA channel access sc ..."
Abstract

Cited by 140 (10 self)
 Add to MetaCart
Wireless mesh networks are expected to be widely used to provide Internet access in the near future. In order to fulfill the expectations, these networks should provide high throughput simultaneously to many users. Recent research has indicated that, due to its conservative CSMA/CA channel access scheme and RTS/CTS mechanism, 802.11 is not suitable to achieve this goal. In this paper, we investigate throughput improvements achievable by replacing CSMA/CA with an STDMA scheme where transmissions are scheduled according to the physical interference model. To this end, we present a computationally efficient heuristic for computing a feasible schedule under the physical interference model and we prove, under uniform random node distribution, an approximation factor for the length of this schedule relative to the shortest schedule possible with physical interference. This represents the first known polynomialtime algorithm for this problem with a proven approximation factor. We also evaluate the throughput and execution time of this algorithm on representative wireless mesh network scenarios through packetlevel simulations. The results show that throughput with STDMA and physicalinterferencebased scheduling can be up to three times higher than 802.11 for the parameter values simulated. The results also show that our scheduling algorithm can schedule networks with 2000 nodes in about 2.5 minutes.
The kNEIGH Protocol for Symmetric Topology Control in Ad Hoc Networks
, 2003
"... Topology control, wherein nodes adjust their transmitting ranges to conserve energy, is an important feature in wireless ad hoc networks. In this paper, we present a topology control protocol that is fully distributed, asynchronous, and localized. This protocol, referred to as the kNEIGH protocol, ..."
Abstract

Cited by 84 (0 self)
 Add to MetaCart
Topology control, wherein nodes adjust their transmitting ranges to conserve energy, is an important feature in wireless ad hoc networks. In this paper, we present a topology control protocol that is fully distributed, asynchronous, and localized. This protocol, referred to as the kNEIGH protocol, maintains the number of neighbors of every node equal to or slightly below a specific value k. Furthermore, the protocol ensures that the resulting communication graph is symmetric, thereby easing the operation of higher protocol layers. To evaluate the performance of the protocol, the value of k that ensures a connected communication graph with high probability is evaluated. It is also shown that, with n nodes in the network, the protocol terminates on every node after exactly 2n messages total and within strictly bounded time. Finally, extensive simulations are carried out, which show that the kNEIGH protocol is about 20% more energyefficient than the most widelystudied existing protocol.
A Case for VariableRange Transmission Power
 Control in Wireless Multihop Networks,” Proc. IEEE INFOCOM
, 2004
"... Abstract—In this paper, we investigate the impact of variablerange transmission power control on the physical and network connectivity, on network capacity, and on power savings in wireless multihop networks. First, using previous work by Steele [18], we show that, for a path attenuation factor 2, ..."
Abstract

Cited by 81 (5 self)
 Add to MetaCart
(Show Context)
Abstract—In this paper, we investigate the impact of variablerange transmission power control on the physical and network connectivity, on network capacity, and on power savings in wireless multihop networks. First, using previous work by Steele [18], we show that, for a path attenuation factor 2, the average range of links in a planar random network of Am2 having n nodes is c ffiffiffi p A n 1. We show that this average range is approximately half the range obtained when commonrange transmission control is used. Combining this result and previous work by Gupta and Kumar [8], we derive an expression for the average traffic carrying capacity of variablerangebased multihop networks. For 2, we show that this capacity remains constant even when more nodes are added to the network. Second, we derive a model that approximates the signaling overhead of a routing protocol as a function of the transmission range and node mobility for both route discovery and route maintenance. We show that there is an optimum setting for the transmission range, not necessarily the minimum, which maximizes the capacity available to nodes in the presence of node mobility. The results presented in this paper highlight the need to design future MAC and routing protocols for wireless ad hoc and sensor networks based, not on commonrange which is prevalent today, but on variablerange power control. Index Terms—Multihop networks, ad hoc networks, traffic capacity, network connectivity, power savings. Ç 1
Phase Transition Phenomena in Wireless Ad Hoc Networks
, 2001
"... There are many contexts in distributed wireless networks where there is a critical threshold, corresponding to a minimum amount of the communication effort or power expenditure by individual nodes, above which a desirable global property exists with high probability. When this individual node ef ..."
Abstract

Cited by 58 (0 self)
 Add to MetaCart
(Show Context)
There are many contexts in distributed wireless networks where there is a critical threshold, corresponding to a minimum amount of the communication effort or power expenditure by individual nodes, above which a desirable global property exists with high probability. When this individual node effort is below the threshold the desired global property exists with a low probability. This "phase transition" is typically seen to become sharper as the number of nodes in the network increases. We discuss in this paper some examples of properties that exhibit such critical behavior: node reachability with probabilistic flooding, adhoc network connectivity, and sensor network coordination. We discuss the connections between these phenomena and the phase transitions that have been shown to arise in random graphs. We argue that a good understanding of these phase transition phenomena can provide useful design principles for engineering distributed wireless networks.
Partial Delaunay Triangulation and Degree Limited Localized Bluetooth
, 2004
"... This paper addresses the problem of localized scatternet formation for multihop Bluetoothbased personal area ad hoc networks. Nodes are assumed to know their positions and are able to establish connections with any of their neighboring nodes, located within their transmission radius, in the neighbo ..."
Abstract

Cited by 56 (14 self)
 Add to MetaCart
This paper addresses the problem of localized scatternet formation for multihop Bluetoothbased personal area ad hoc networks. Nodes are assumed to know their positions and are able to establish connections with any of their neighboring nodes, located within their transmission radius, in the neighbor discovery phase. The next phase of the proposed formation algorithm is optional and can be applied to construct a sparse geometric structure in a localized manner. We propose here a new sparse planar structure, namely, partial Delaunay triangulation (PDT), which can be constructed locally and is denser than other known localized planar structures. In the next mandatory phase, the degree of each node is limited to seven by applying the Yao structure, and the masterslave relations in piconets are formed in created subgraphs. This phase consists of several iterations. In each iteration, undecided nodes with higher keys than any of their undecided neighbors apply the Yao structure to bound the degrees, decide masterslave relations on the remaining edges, and inform all neighbors about either deleting edges or masterslave decisions. To the best of our knowledge, our schemes are the first schemes that construct degree limited (a node has at most seven slaves) and connected piconets in multihop networks, without parking any node. The creation and maintenance require small overhead in addition to maintaining accurate location information for onehop neighbors. The experiments confirm good functionality of created Bluetooth networks in addition to their fast creation and straightforward maintenance.
Coverage and Connectivity of Ad Hoc Networks in Presence of Channel Randomness
 in Proc. IEEE INFOCOM 2005
, 2005
"... In this paper, we present an analytical procedure for the computation of the node isolation probability in an ad hoc network in the presence of channel randomness, with applications to shadowing and fading phenomena. Such a probability coincides with the complement of the coverage probability, given ..."
Abstract

Cited by 53 (4 self)
 Add to MetaCart
In this paper, we present an analytical procedure for the computation of the node isolation probability in an ad hoc network in the presence of channel randomness, with applications to shadowing and fading phenomena. Such a probability coincides with the complement of the coverage probability, given that nodes are distributed according to a Poisson point process. These results are used to obtain an estimate of the connectivity features for very dense networks. For the case of superimposed lognormal shadowing and Rayleigh fading, the connectivity improvements achievable by means of diversity schemes are investigated.
The critical transmitting range for connectivity in mobile ad hoc networks
 IEEE Transactions on Mobile Computing
, 2005
"... this paper, we study the critical transmitting range (CTR) for connectivity in mobile ad hoc networks. We prove that ln n rM c n for some constant c 1, where rM is the CTR in the presence of Mlike node mobility and n is the number of network nodes. Our result holds for an arbitrary mobility model ..."
Abstract

Cited by 48 (3 self)
 Add to MetaCart
(Show Context)
this paper, we study the critical transmitting range (CTR) for connectivity in mobile ad hoc networks. We prove that ln n rM c n for some constant c 1, where rM is the CTR in the presence of Mlike node mobility and n is the number of network nodes. Our result holds for an arbitrary mobility model M such that: 1) M is obstacle free and 2) nodes are allowed to move only within a certain bounded area. We also investigate in detail the case of random waypoint mobility, which is the most common mobility model used in the simulation of ad hoc networks. Denoting with rw p the CTR with random waypoint mobility when the pause time is set to p and node velocity is set to v, we prove that rw qffiffiffiffiffi pþ0:521405 v ln n p p n if p>0 and that rw qffiffiffiffiffi ln n 0 n. The results of our simulations also suggest that if n is large enough (n 50), rw r 0 is well approximated by 4 ln n, where r is the critical range in case of uniformly distributed nodes. The results presented in this paper provide a better understanding of the behavior of a fundamental network parameter in the presence of mobility and can be used to improve the accuracy of mobile ad hoc network simulations. Index Terms—Critical transmitting range, connectivity, random waypoint model, mobility modeling, ad hoc networks. æ 1