Number Of Transmitted Messages Research Articles

A NEW DISTRIBUTED LOCATION-BASED ROUTING ALGORITHM FOR WIRELESS SENSOR NETWORKS

Searching and routing procedures are important in order to ensure communication in wireless sensor networks (WSN). Although naive flooding-based searching is simple to implement, it costs a high number of message transmissions and results in high energy consumption. In this study, we propose a new distributed location-based routing algorithm for WSN. Our goal was to decrease the number of message transmissions and to increase coverage by constructing relay zones. Directed broadcast, relay zone, and broadcast suppression constitute the backbone of our algorithm. We compared our algorithm with a flooding-based approach, and saw that our algorithm performs much better for several parameters.

Communication-efficient processing of multiple continuous aggregate queries

Abstract Recently, great attention has been paid to distributed stream processing systems (DSPSs), where a number of distributed source nodes generate data streams and queries are continuously executed over those streams. An emerging challenge in large-scale DSPSs is to efficiently process multiple continuous aggregate queries. To process a continuous aggregate query, each source node periodically sends partial aggregates computed over its local stream to the sink node, where the final results are computed. Since sending partial aggregates for each query separately can lead to significant communication overhead, lowering the overall performance and scalability, multiple aggregate queries must be processed collectively, rather than separately. In this paper, we propose an efficient method for collectively processing multiple continuous aggregate queries, which minimizes the total communication costs from source nodes to the sink node. The proposed method finds the smallest set of partial aggregates that each source node needs to send to the sink node to correctly answer all the queries, and thus minimizes the number of message transmissions. Furthermore, since the proposed method operates on-the-fly, it can efficiently handle registration or deregistration of queries at any time. Through theoretical analysis and experiments, we show that the proposed method outperforms the existing ones in terms of communication costs.

An Energy-Efficient Data Gathering Mechanism using Traveling Wave and Spatial Interpolation for Wireless Sensor Networks

Wireless sensor network technologies have attracted a lot of attention in recent years. In this paper, we propose an energy-efficient data gathering mechanism using traveling wave and spatial interpolation for wireless sensor networks. In our proposed mechanism, sensor nodes schedule their message transmission timing in a fully-distributed manner such that they can gather sensor data over a whole wireless sensor network and transmit that data to a sink node while switching between a sleep state and an active state. In addition, each sensor node determines the redundancy of its sensor data according to received messages so that only necessary sensor data are gathered and transmitted to the sink node. Our proposed mechanism does not require additional control messages and enables both data traffic and control traffic to be drastically reduced. Through simulation experiments, we confirmed that with our proposed mechanism, the number of message transmissions can be reduced by up to 77% and the amount of transmitted data can be reduced by up to 13% compared to a conventional mechanism.

Energy-Efficient Dynamic Query Routing Tree Algorithm for Wireless Sensor Networks

To exploit in answering queries generated by the sink for the sensor networks, we propose an efficient routing protocol called energy-efficient dynamic routing tree (EDRT) algorithm. The idea of EDRT is to maximize in-network processing opportunities using the parent nodes and sibling nodes. In-network processing reduces the number of message transmission by partially aggregating results of an aggregate query in intermediate nodes, or merging the results in one message. This results in reduction of communication cost. Our experimental results based on simulations prove that our proposed method can reduce message transmissions more than query specific routing tree (QSRT) and flooding-based routing tree (FRT).

A Key Re-Distribution and Authentication Based Technique for Secured Communication in Clustered Wireless Sensor Networks with Node Mobility

Due to application of WSN in mission critical areas, secured message communication is very important. We have attempted to present a methodology that ensures secured communication among nodes in a hierarchical Cluster Based WSN. Our scheme works when member sensor nodes move from one Cluster Head (CH) to another. The proposed scheme is based on Key Redistribution during node mobility and development of an Authentication Model to check whether the new node in a cluster is an intruder. We have carried out extensive simulation experiments, which demonstrate the efficacy of the proposed scheme. The experiments suggest that the number of message transmission in creases linearly with the number of mobile nodes during key-redistribution when a node moves from one CH to another. We have seen that the detection efficiency of the Authentication Model is 0.9 to 1 when tunable threshold value is 0.02 and sensor nodes are sufficiently mobile.

Energy-Efficient Reprogramming of a Swarm of Mobile Sensors

Existing code update protocols for reprogramming nodes in a sensor network are either unsuitable or inefficient when used in a mobile environment. The prohibitive factor of uncertainty about a node's location due to their continuous movement coupled with the obvious constraint of a node's limited resources, pose daunting challenges to the design of an effective code dissemination protocol for mobile sensor networks. In this paper, we propose ReMo, an energy-efficient, multihop reprogramming protocol for mobile sensor networks. Without making any assumptions on the location of nodes, ReMo uses the LQI and RSSI measurements of received packets to estimate link qualities and relative distances with neighbors in order to select the best node for code exchange. The protocol is based on a probabilistic broadcast paradigm with the mobile nodes smoothly modifying their advertisement transmission rates based on the dynamic changes in network density, thereby saving valuable energy. Contrary to previous protocols, ReMo downloads pages regardless of their order, thus, exploiting the mobility of the nodes and facilitating a fast transfer of the code. Our simulation results show significant improvement in reprogramming time and number of message transmissions over other existing protocols under different settings of network mobility. Our implementation results of ReMo on a testbed of SunSPOTs also showcase its better performance than existing reprogramming protocols in terms of transfer time and number of message transmissions.

Adaptive aggregation tree transformation for energy-efficient query processing in sensor networks

Data aggregation reduces energy consumption by reducing the number of message transmissions in sensor networks. Effective aggregation requires that event messages be routed along common paths. While existing routing protocols provide many ways to construct the aggregation tree, this opportunistic style of aggregation is usually not optimal. The Minimal Steiner Tree (MST) maximises the possible degree of aggregation, but finding such a tree requires global knowledge of the network, which is not practical in sensor networks. In this paper, we propose the Adaptive Aggregation Tree (AAT) to dynamically transform the structure of the routing tree to improve the efficiency of data aggregation. It adapts to changes in the set of source nodes automatically, and approaches the cost savings of MST without explicit maintenance of an infrastructure. The evaluation results show that AAT reduces the communication energy consumption by 23%, compared to shortest-path tree, and by 31%, compared to GPSR.

TIGHTER TIME BOUNDS ON BROADCASTING IN TORUS NETWORKS IN PRESENCE OF DYNAMIC FAULTS

We consider the problem of broadcasting in a network G under the hypothesis that each vertex can inform in one unit of time all of its neighbours and that any number of message transmissions, less than the edge-connectivity of G, may fail during each time unit. In particular, we study broadcasting in the n-dimensional k-ary torus, a popular topology for link connections in communication networks. We prove that under the above strong fault-assumption, if k is even and polynomially limited in n, and n is sufficient large, broadcasting in the n-dimensional k-ary torus can be accomplished in time [Formula: see text], where [Formula: see text] is the diameter of the n-dimensional k-ary torus.

Tighter Time Bounds on Broadcasting in Torus Networks in Presence of Dynamic Faults

We consider the problem of broadcasting in a network G under the hypothesis that each vertex can inform in one unit of time all of its neighbours and that any number of message transmissions, less than the edge-connectivity of G, may fail during each time unit. In particular, we study broadcasting in the n-dimensional k-ary torus, a popular topology for link connections in communication networks. We prove that under the above strong fault-assumption, if k is even and polynomially limited in n, and n is sufficient large, broadcasting in the n-dimensional k-ary torus can be accomplished in time , where is the diameter of the n-dimensional k-ary torus.

Minimum time broadcast in faulty star networks

In this paper we give new results on the fault-tolerance capabilities of the star graph. We first consider the problem of determining the maximum number r(n) of vertices in a n! vertices star graph S n such that by removing any set of vertices and/or edges from S n of cardinality at most r(n) the diameter of S n does not increase. Subsequently, we give an algorithm for broadcasting a message in S n in optimal time (the diameter of S n ) and using the minimum possible number of message transmissions, i.e., n! − 1, in presence of up to r(n) vertex or edge faults, assuming the set of faults is known to all vertices of the network. We also extend this result to the case in which there is no global knowledge on the faulty elements.

Efficient Communication in Folded Petersen Networks

Fast and efficient communication is one of the most important requirements in today's multicomputers. When reaching a larger scale of processors, the probability of faults in the network increases, hence communication must be robust and fault tolerant. The recently introduced family of folded Petersen networks, constructed by iteratively applying the cartesian product operation on the well-known Petersen graph, provides a regular, node– and edge-symmetric architecture with optimal connectivity (hence maximal fault-tolerance), and logarithmic diameter. Compared to the closest sized hypercube, the folded petersen network has a smaller diameter, lower node degree and higher packing density. In this paper, we study fundamental communication primitives like single routing, permutation routing, one-to-all broadcasting, multinode-broadcasting (gossiping), personalized communications like scattering, and total exchange on the folded Petersen networks, considering two communication models, namely single link availability (SLA) and multiple link availability (MLA). We derive lower bounds for these problems and design optimal algorithms in terms of both time and the number of message transmissions. The results are based on the construction of minimal height spanning trees in the fault-free folded Petersen network. We further analyze these communication primitives in faulty networks, where processing nodes and transmission links cease working. This analysis is based on multiple arc-disjoint spanning trees, a construct also useful for analyzing other families of multicomputer networks.

Optimal Communication Primitives on the Generalized Hypercube Network

Efficient interprocessor communication is crucial to increasing the performance of parallel computers. In this paper, a special framework is developed on thegeneralized hypercube, a network that is currently receiving considerable attention. Using this framework as the basic tool, a number of spanning subgraphs with special properties to fit various communication needs are constructed on the network. The importance of these spanning subgraphs is demonstrated with the development of optimal algorithms for four fundamental communication problems, namely, theone-to-allandall-to-all broadcastingand theone-to-allandall-to-all scattering. Broadcastingis the distribution of the same group of messages from a source processor to all other processors, andscatteringis the distribution of distinct groups of messages from a source processor to each other processor. We consider broadcasting and scattering from a single processor of the network (one-to-all broadcasting and scattering) and simultaneously from all processors of the network (all-to-all broadcasting and scattering). For the all-to-all broadcasting and scattering algorithms, a special technique is developed on the generalized hypercube so that messages originating at individual nodes are interleaved in such a manner that no two messages contend for the same edge at any given time. The communication problems are studied under thestore-and-forward, all-portcommunication model. Lower bounds are derived for the above problems under the stated assumptions, in terms of time and number of message transmissions, and optimal algorithms are designed.

Optimal Communication Algorithms on Star Graphs Using Spanning Tree Constructions

In this paper we consider three fundamental communication problems on the star interconnection network: the problem of simultaneous broadcasting of a message from every node to all other nodes, or multinode broadcasting, the problem of a single node sending distinct messages to each one of the other nodes, or single-node scattering, and finally the problem of each node sending distinct messages to every other node, or total exchange. All of these problems are studied under two different assumptions: the assumption that each node can transmit a message of fixed length to one of its neighbors and simultaneously receive a message of fixed length from one of its neighbors (not necessarily the same one) at each time step, or single-link availability, and the assumption that each node can exchange messages of fixed length with all of its neighbors at each time step, or multiple-link availability. In both cases communication is assumed to be bidirectional. The cases where the originating processor wishes to send only one or more than one message to each one of the other processors are distinguished when necessary. Lower bounds are derived for these problems under the stated assumptions, and optimal algorithms are designed in terms of both time and number of message transmissions. Although the algorithms derived for the first two problems require the minimum amount of the above resources, the algorithm designed for the total exchange problem is optimal only to within a multiplicative factor. All the communication algorithms presented in this paper are based on the construction of spanning trees with special properties on the star graph to fit different communication needs. A special framework is developed to facilitate the construction of these trees. The scheduling disciplines that lead to optimal results in each case are described.

Distributed algorithm for extrema-finding in circular configuration of processors

A distributed algorithm for finding the leader (highest numbered node) of a circular configuration of n processors is presented. Bounds on the number of message transmissions are derived. The average number of messages transmitted is of O( n ln n).