Passive clustering does not employ control packets to collect topological information in ad hoc networks. In our proposal, we avoid making frequent changes in cluster architecture due to repeated election and re-election of cluster heads and gateways. Our primary objective has been to make Passive Clustering more practical by employing optimal number of gateways and reduce the number of rebroadcast packets.
Key pre-distribution is an important area of research in Distributed Sensor Networks (DSN). Two sensor nodes are considered connected for secure communication if they share one or more common secret key(s). It is important to analyze the largest subset of nodes in a DSN where each node is connected to every other node in that subset (i.e., the largest clique). This parameter (largest clique size) is important in terms of resiliency and capability towards efficient distributed computing in a DSN. In this paper, we concentrate on the schemes where the key pre-distribution strategies are based on transversal design and study the largest clique sizes. We show that merging of blocks to construct a node provides larger clique sizes than considering a block itself as a node in a transversal design.
Optical splitting capability at some nodes is necessary to get efficient multicast routing in the wavelength routed wavelength division multiplexing (WDM) networks. There is a growing interest in efficiently protecting multicast sessions against the failure of network components. We propose algorithms for protecting multicast sessions against failure of network components such as links and nodes in a network with sparse splitting and sparse wavelength conversion. The effectiveness of the proposed algorithms is verified through extensive simulation experiments.
We identify a type of distributed system where the notion of space in planning is important. We give a formal modeling of the distributed system where planning is done. We show that several interesting planning goals in the model can be specified in a spatio-temporal logic STL. We develop an efficient planning procedure for these goals in the distributed setting.
Most of the past researches [1], [2], [3] investigate the behavior of distributed real time commit protocols either under update or blind write model. The effect of both types of models has not been investigated collectively. These protocols also require a considerable amount of memory for maintaining temporary objects (data structure) created during execution of transactions and block the WORKDONE message if cohort is dependent. This paper presents an optimized distributed real time commit protocol (MEFCP) based on new locking scheme and write operation divided into update and blind write. The proposed protocol optimizes the memory required for maintaining the transient information of lender & borrower [1]. It also sends the WORKDONE message if borrower has locked the data in mode 2 only. We also compared MEFCP with PROMPT and 2SC commit protocols through simulation.
The fundamental question considered in this paper is when program Q, if executed immediately after program P, is guaranteed not to interfere with P and be safe from interference by P. If a message sent by one of these programs is received by the other, it may affect and modify the other’s execution. The notion of communication closed layers (CCLs) introduced by Elrad and Francez in 1982 is a useful tool for studying such interference. CCLs have been considered mainly in the context of reliable FIFO channels (without duplication), where one can design programs layers that do not interfere with any other layer. When channels are less than perfect such programs are no longer feasible. The absence of interference between layers becomes context-dependent. In this paper we study the impact of message duplication and loss on the safety on the safety of layer composition. Using a communication phase operator, the fits after relation among programs is defined. If program Q fits after P then P and Q will not interfere with each other in executions of P∗Q. For programs P and Q in a natural class of programs we outline efficient algorithms for the following: (1) deciding whether Q fits after P; (2) deciding whether QsealsP, meaning that Q fits after P and no following program can communicate with P; and (3) constructing a separatorS that both fits after P and satisfies that Q fits after P∗S.
We present a new approach to find a collision-free transmission schedule for mobile ad hoc networks (MANETs) in a TDM environment. A hexagonal cellular structure is overlaid on the MANET and then the actual demand for the number of slots in each cell is found out. We assume a 2-cell buffering in which the interference among different mobile nodes do not extend beyond cells more than distance 2 apart. Based on the instantaneous cell demands, we propose optimal slot assignment schemes for both homogeneous (all cells have the same demand) and non-homogeneous cell demands by a clever reuse of the time slots, without causing any interference. The proposed algorithms exploit the hexagonal symmetry of the cells requiring O(log log m + mD + n) time, where m is the number of mobile nodes in the ad hoc network, n and D being the number of cells and diameter of the cellular graph.
Authors in [1] have recently introduced an interesting model, COSMOS (Cluster-based heterOgeneouS MOdel for Sensor networks) for sensor networks; COSMOS is a hierarchical network architecture that consists of a large number of low cost sensors with very limited computation capability and a smaller number of more powerful "clusterheads". The clusterheads can communicate between each other in an asynchronous fashion while the low capability sensors under each clusterhead operate in a synchronous way with their respective clusterheads. Our purpose in the present paper is to design several protocols for benchmark programs like broadcast, matrix multiplication and matrix chain multiplication using this model and provide detailed complexity analysis of these protocols. Our results further illustrates the usefulness of the model for use in sensor networks.
Energy efficient self-organization is a crucial method to prolong the lifetime of wireless sensor networks consisting of energy constrained sensor nodes. In this paper, we focus on a distributed node scheduling scheme to extend network lifespan. We discuss the network coverage performance when sensor nodes are deployed according to Poisson point process and reveal the internal relationship among the required coverage performance, expected network lifetime and the intensity of Poisson point process. Also the impact of uniformly distributed time asynchrony on network coverage performance is analyzed. Simulation results demonstrate that the proposed scheme works well in the presence of time asynchrony.
Recently there have been a number of efforts to study issues related to coordination and control algorithms for systems of multiple autonomous mobile robots (also known as robot swarms) from the viewpoint of distributed computing. This paper reviews the literature in the area and discusses some open problems and future research directions.
Research in embedded networked sensing has primarily focused on the design of hardware architectures for sensor nodes and infrastructure protocols for long lived operation of resource constrained sensor network deployments. There is now an increasing interest in the programming aspects of sensor networks, especially in the broader context of pervasive computing. This paper provides a brief overview of ongoing research in programming of sensor networks and classifies it into layers of abstraction that provide the application developer with progressively higher level primitives to express distributed, phenomenon-centric collaborative computation. As a specific instance of a macroprogramming methodology, we discuss the data driven Abstract Task Graph (ATaG) model and the structure of its underlying runtime system. ATaG separates the application functionality from non-functional aspects, thereby enabling end-to-end architecture-independent programming and automatic software synthesis for a class of networked sensor systems. A prototype visual programming, software synthesis, functional simulation and visualization environment for ATaG has been implemented.
Data streams from sensors are usually characterized as continuous, with very frequent updates. Queries over those data streams need to be processed in near real-time. So it is needed to design the index structure for supporting the frequent updates and fast retrieval of data efficiently. In this paper, CLUR-Tree (Cache-conscious Lazy Update R-Tree) is proposed, which is a spatial index for efficient processing of frequent updates of data streams in locality preserving monitoring applications. CLUR-Tree has two characteristics. First, it excludes index reconstruction overhead by permitting modification of only the index node of the sensor which moves out of the corresponding MBR (Minimum Bound Rectangle). Second, it reduces the key spaces by applying new compression method for MBR used as key in R-Tree and by considering cache to prevent bottleneck due to speed difference between main memory and CPU. The experimental results indicate that the proposed CLUR-Tree enhances update performance and gives a good retrieval performance simultaneously.
Sensor networks are increasingly being used for applications which require fast processing of data, such as multimedia processing. Distributed computing can be used on a sensor network to reduce the completion time of a task and distribute the energy consumption equitably across all sensors. The distribution of task modules to sensors should consider not only the time and energy savings, but must also improve reliability of the entire task execution. We formulate the above as an optimization problem, and use the A* algorithm with improvements to determine an optimal static allocation of modules among a set of sensors. We also suggest a faster but suboptimal algorithm, called the greedy A* algorithm. Both algorithms have been simulated, and the results have been compared in terms of energy savings, decrease in completion time of the task, and the deviation of the sub-optimal solution from the optimal one. The sub-optimal solution required 8-35% less computation, at the cost of 2.5-15% deviation from the optimal solution in terms of average energy spent per sensor node. Both the A* and greedy A* algorithms have been shown to distribute energy consumption more uniformly across sensors than centralized execution. The greedy A* algorithm is found to be scalable, as the number of evaluations in determining the allocation increases linearly with the number of sensors.
This paper presents a new location management scheme that integrates two key ideas, namely, (i) Subscriber Movement Profile (SMP) based on spatial and temporal locality of the movement of a mobile terminal and (ii) localized updates known as Time-bound Self Purging Indicators (TSPI) generated by a probabilistic approach when a mobile terminal does not adhere to registered profile. The SMP registered by a mobile host is used to predict its cell location based on time specific movement history. The transient deviations from the registered SMP are handled efficiently by TSPIs using a Regional Route Map (RRM).
Most of the proposed algorithms in ad hoc networks assume homogeneous nodes with similar transmission range and capabilities. However, in heterogeneous ad hoc networks, it is not necessary that all nodes have bidirectional link with each other and hence, those algorithms may not perform well while deployed in real situations. In this paper, we propose a scheme for an ad hoc on-demand routing protocol which utilizes the unidirectional links during the data transmission. Simulation shows that it is not only possible to use unidirectional links but it is also better in terms of performance metrics we defined in different situations.
In this paper a fault tolerant routing algorithm for unicasting on star graph is proposed. The routing algorithm does not involve back tracking and uses fault-vectors. Each node in an n-star has a fault-vector of $\lfloor\frac{3(n-1)}{2}\rfloor$ bits. The kth bit of a node’s fault-vector is a measure of its routing ability to nodes which are at distance k from itself. The fault-vector of each node can easily be calculated through $\lfloor\frac{3(n-1)}{2}\rfloor$ rounds of information exchanges among neighbor nodes. For a given source destination pair (u,v), the routing algorithm finds a path of length d + h where d is the length of the shortest path between u and v in a fault-free star graph and h = 0, 2 or 4. The space requirement for storing the fault vector is O(n) in each node. Simulation results show that the proposed algorithm far outperforms the routing algorithm based on safety vectors [13].
Distributed methodologies to find pareto-optimal frontier with concern to privacy, of objectives and constraints, of parties is of interest in scenarios like negotiations. Adaptation of lagrangian method to solve distributed weighting method for both strictly concave and not strictly concave (e.g. linear) value functions is proposed for a maximization problem.
Location area (LA) planning in PCSN is a NP-hard problem. In this paper we modeled it as a clustering problem where each LA is considered to be a cluster. Agglomerative Hierarchical Algorithm (AHA) is applied to form the cell clusters. The algorithm starts assuming each cell as a separate cluster. In successive iterations the clusters are merged randomly in a bottom up fashion based on a total cost function (TCF) till the desired numbers of clusters are obtained. Total Cost Evaluation Metric (TCEM) is proposedto compare AHA with other schemes. Experimental results show that AHA provides better results in most of the cases compared to Greedy Heuristic based approach.
Over the past decade, a pair of instructions called load-linked (LL) and store-conditional (SC) have emerged as the most suitable synchronization instructions for the design of lock-free algorithms. However, current architectures do not support these instructions; instead, they support either CAS (e.g., UltraSPARC, Itanium) or restricted versions of LL/SC (e.g., POWER4, MIPS, Alpha). To bridge this gap, a flurry of algorithms that implement LL/SC from CAS have appeared in the literature. Some of these algorithms assume that N, the maximum number of participating processes, is fixed and known in advance. Others make no such assumption, but are either non-blocking (not wait-free), implement small LL/SC objects, or require that a process performs O(N) work to join the algorithm. Specifically, no constant-time, word-sized, wait-free LL/SC algorithm that does not require the knowledge of N exists. In this paper, we present such an algorithm.
The wide availability of mobile devices together with the technical possibility to form ad-hoc networks paves the way for building highly dynamic communicating communities of mobile users. A challenge is how to deliver messages in such networks incurring least routing overhead. Cooperative routing is a mobile-agent assisted team approach, which utilizes a set of fixed cluster head nodes to provide proper coordination and cooperation for exchanges and sharing of messages in the team. Our routing strategy aims at reducing routing overheads, message traffic and unnecessary random node visits in the network for delivering data. The main benefit provided by cooperative routing is considerable network traffic reduction at high load. We highlight the main components of the system and discuss the agent life cycle in detail together with the parameters and strategies governing the migration of agents, their merging and termination.
