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Adaptive Protocols for Information Dissemination in Wireless Sensor Networks
, 1999
"... In this paper, we present a family of adaptive protocols, called SPIN (Sensor Protocols for Information via Negotiation) , that eciently disseminates information among sensors in an energyconstrained wireless sensor network. Nodes running a SPIN communication protocol name their data using highlev ..."
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Cited by 514 (9 self)
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In this paper, we present a family of adaptive protocols, called SPIN (Sensor Protocols for Information via Negotiation) , that eciently disseminates information among sensors in an energyconstrained wireless sensor network. Nodes running a SPIN communication protocol name their data using highlevel data descriptors, called metadata. They use metadata negotiations to eliminate the transmission of redundant data throughout the network. In addition, SPIN nodes can base their communication decisions both upon applicationspecic knowledge of the data and upon knowledge of the resources that are available to them. This allows the sensors to eciently distribute data given a limited energy supply. We simulate and analyze the performance of two specic SPIN protocols, comparing them to other possible approaches and a theoretically optimal protocol. We nd that the SPIN protocols can deliver 60% more data for a given amount of energy than conventional approaches. We also nd that, in terms...
Negotiationbased Protocols for Disseminating Information in Wireless Sensor Networks
 Wireless Networks
, 2002
"... Abstract. In this paper, we present a family of adaptive protocols, called SPIN (Sensor Protocols for Information via Negotiation), that efficiently disseminate information among sensors in an energyconstrained wireless sensor network. Nodes running a SPIN communication protocol name their data usi ..."
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Cited by 181 (3 self)
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Abstract. In this paper, we present a family of adaptive protocols, called SPIN (Sensor Protocols for Information via Negotiation), that efficiently disseminate information among sensors in an energyconstrained wireless sensor network. Nodes running a SPIN communication protocol name their data using highlevel data descriptors, called metadata. They use metadata negotiations to eliminate the transmission of redundant data throughout the network. In addition, SPIN nodes can base their communication decisions both upon applicationspecific knowledge of the data and upon knowledge of the resources that are available to them. This allows the sensors to efficiently distribute data given a limited energy supply. We simulate and analyze the performance of four specific SPIN protocols: SPINPP and SPINEC, which are optimized for a pointtopoint network, and SPINBC and SPINRL, which are optimized for a broadcast network. Comparing the SPIN protocols to other possible approaches, we find that the SPIN protocols can deliver 60 % more data for a given amount of energy than conventional approaches in a pointtopoint network and 80 % more data for a given amount of energy in a broadcast network. We also find that, in terms of dissemination rate and energy usage, the SPIN protocols perform close to the theoretical optimum in both pointtopoint and broadcast networks.
HighPerformance Communication Networks
"... Contents 1 Wireless Networks 1 1.1 Introduction ...................................... 1 1.1.1 History of Wireless Networks ........................ 2 1.1.2 Wireless Data Vision ............................. 5 1.1.3 Technical Challenges ............................. 7 1.2 The Wireless Channel ...... ..."
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Cited by 135 (4 self)
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Contents 1 Wireless Networks 1 1.1 Introduction ...................................... 1 1.1.1 History of Wireless Networks ........................ 2 1.1.2 Wireless Data Vision ............................. 5 1.1.3 Technical Challenges ............................. 7 1.2 The Wireless Channel ................................. 8 1.2.1 Path loss ................................... 9 1.2.2 Shadow Fading ................................ 10 1.2.3 Multipath Flatfading and Intersymbol Interference ............. 11 1.2.4 Doppler Frequency Shift ........................... 12 1.2.5 Interference .................................. 13 1.2.6 Infrared versus Radio ............................ 13 1.2.7 Capacity Limits of Wireless Channels .................... 14 1.3 Link Level Design .................................. 15 1.3.1 Modulation Techniques ............................ 15 1.3.2 Channel Coding and Link Layer Retransmission .............. 16 1.3.3 FlatFading Countermeasures ..
Power Consumption in Packet Radio Networks
 THEORETICAL COMPUTER SCIENCE
, 1997
"... In this paper we study the problem of assigning transmission ranges to the nodes of a multihop packet radio network so as to minimize the total power consumed under the constraint that adequate power is provided to the nodes to ensure that the network is strongly connected (i.e., each node can co ..."
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Cited by 118 (1 self)
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In this paper we study the problem of assigning transmission ranges to the nodes of a multihop packet radio network so as to minimize the total power consumed under the constraint that adequate power is provided to the nodes to ensure that the network is strongly connected (i.e., each node can communicate along some path in the network to every other node). Such assignment of transmission ranges is called complete. We also consider the problem of achieving strongly connected bounded diameter networks.
On the complexity of computing minimum energy consumption broadcast subgraphs
 in Symposium on Theoretical Aspects of Computer Science
, 2001
"... Abstract. We consider the problem of computing an optimal range assignment in a wireless network which allows a specified source station to perform a broadcast operation. In particular, we consider this problem as a special case of the following more general combinatorial optimization problem, calle ..."
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Cited by 96 (11 self)
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Abstract. We consider the problem of computing an optimal range assignment in a wireless network which allows a specified source station to perform a broadcast operation. In particular, we consider this problem as a special case of the following more general combinatorial optimization problem, called Minimum Energy Consumption Broadcast Subgraph (in short, MECBS): Given a weighted directed graph and a specified source node, find a minimum cost range assignment to the nodes, whose corresponding transmission graph contains a spanning tree rooted at the source node. We first prove that MECBS is not approximable within a constant factor (unless P=NP). We then consider the restriction of MECBS to wireless networks and we prove several positive and negative results, depending on the geometric space dimension and on the distancepower gradient. The main result is a polynomialtime approximation algorithm for the NPhard case in which both the dimension and the gradient are equal to 2: This algorithm can be generalized to the case in which the gradient is greater than or equal to the dimension. 1
Adaptive coding for timevarying channels using outdated fading estimates
 IEEE Trans. Commun
, 1999
"... ..."
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, ..."
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Cited by 65 (0 self)
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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.
Predictive and Adaptive Bandwidth Reservation for HandOffs in QoSSensitive Cellular Networks
 in Proc. ACM SIGCOMMâ€™98
, 1998
"... How to control handoff drops is a very important Qualityof Service (QoS) issue in cellular networks. In order to keep the handoff dropping probability below a prespecified target value (thus providing a probabilistic QoS guarantee), we design and evaluate predictive and adaptive schemes for the ..."
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Cited by 63 (6 self)
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How to control handoff drops is a very important Qualityof Service (QoS) issue in cellular networks. In order to keep the handoff dropping probability below a prespecified target value (thus providing a probabilistic QoS guarantee), we design and evaluate predictive and adaptive schemes for the bandwidth reservation for the existing connections' handoffs and the admission control of new connections. We first develop a method to estimate user mobility based on an aggregate history of handoffs observed in each cell. This method is then used to predict (probabilistically) mobiles' directions and handoff times in a cell. For each cell, the bandwidth to be reserved for handoffs is calculated by estimating the total sum of fractional bandwidths of the expected handoffs within a mobilityestimation time window. We also develop an algorithm that controls this window for efficient use of bandwidth and effective response to (1) timevarying traffic/mobility and (2) inaccuracy of mobility...
Hardness Results for the Power Range Assignment Problem in Packet Radio Networks
 in proceedings of RANDOM/APPROX
, 1999
"... Abstract. The minimum range assignment problem consists of assigning transmission ranges to the stations of a multihop packet radio network so as to minimize the total power consumption provided that the transmission range assigned to the stations ensures the strong connectivity of the network (i.e ..."
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Cited by 52 (14 self)
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Abstract. The minimum range assignment problem consists of assigning transmission ranges to the stations of a multihop packet radio network so as to minimize the total power consumption provided that the transmission range assigned to the stations ensures the strong connectivity of the network (i.e. each station can communicate with any other station by multihop transmission). The complexity of this optimization problem was studied by Kirousis, Kranakis, Krizanc, and Pelc (1997). In particular, they proved that, when the stations are located in a 3dimensional Euclidean space, the problem is NPhard and admits a 2approximation algorithm. On the other hand, they left the complexity of the 2dimensional case as an open problem. As for the 3dimensional case, we strengthen their negative result by showing that the minimum range assignment problem is APXcomplete, so, it does not admit a polynomialtime approximation scheme unless P=NP. We also solve the open problem discussed by Kirousis et al by proving that the 2dimensional case remains NPhard. 1