14357490
A Distributed Self-Stabilizing Algorithm for Finding a Connected Dominating Set in a Graph
A connected dominating set of a graph G is a set of nodes of G such that every node in G is either in the set or is adjacent to some node in the set, and the graph induced by the elements of the set is connected. Connected dominating sets have major applications in routing in wireless ad-hoc networks. In this paper, we present a distributed self-stabilizing algorithm for finding a connected dominating set of a graph. Starting from an arbitrary initial state, the algorithm finds a connected dominating set in O(N^2) time, where N is the number of nodes. We also show detailed simulation results to indicate that in practice, the algorithm finds small-sized connected dominating sets in a short time.
32945610
A Framework for Automatic Identification of the Best Checkpoint and Recovery Protocol
Fault tolerance is important for a distributed system to increase its reliability and throughput. Checkpoint and recovery protocols have been proposed as fault tolerance for non-critical applications. The performance of checkpoint and recovery protocols plays an important role in the overall performance of a distributed system. The performance of these protocols depends on system characteristics as well as an application characteristics. In this paper, we propose a novel technique to automatically identify the checkpoint and recovery protocol which is likely to perform the best for a given system and an application the system is currently running. We present experimental results to show that the scheme can efficiently determine a suitable checkpoint and recovery protocol for many applications.
65058359
Group Based Routing in Disconnected Ad Hoc Networks
In this paper, we propose a routing protocol for disconnected ad hoc networks where most nodes tend to move about in groups. To the best of our knowledge, no routing protocol for disconnected ad hoc networks has been designed earlier keeping in mind possible group patterns formed by the movement of nodes. Our protocol works by identifying groups using an efficient distributed group membership protocol, and then routing at the group level, rather than at the node level. The protocol is designed so that existing concepts of routing in disconnected ad hoc networks can be extended to work at the group level. Initial simulations across a broad spectrum of parameters suggest that our protocol performs better in terms of delivery ratio and latency over traditional approaches like AODV [1], and also over disconnected routing approaches like the 2-Hop routing protocol [2].
19017935
Fault-containing network protocols
Self-stabilization is a simple and elegant approach towards designing fault-tolerant network protocols. While self-stabilization provides automatic recovery from arbitrary transient faults, self-stabilizing systems do not incorporate any optimization for more efficient recovery from limited transient faults, even though such limited faults are more likely to occur in practice than arbitrary faults. Fault-containing self-stabilizing protocols are proposed to efficiently contain the effects of more frequent, limited transient faults while retaining the desirable property of self-stabilization. In this paper, we propose a methodology for designing fault-containing selfstabilizing network protocols. The methodology views the properties of self-stabilization and fault-containment in separation. Since self-stabilizing protocols already exist for many important network problems, the design starts with an existing self-stabilizing protocol, and adds to it the fault-containment property. The feasibilitv of this technique is illustrated bv the design of a fault-containing self-stabilizing protocol for the breadthfirst-search (BFS) spanning tree problem. The applicability of the technique used in deriving the BFS protocol to other problems is also discussed.
9811083
Performance enhancement of a contract net protocol based system through instance-based learning
The contract net protocol (CNP) is a widely used coordination mechanism in multiagent systems. It has a lot of communication overhead due to the broadcast of the task announcements. The performance of the CNP degrades drastically when the number of communicating agents and the number of tasks announced increases. Hence, it has problems of scalability. In order to overcome this limitation, an instance-based learning (IBL) mechanism is designed that uses previously stored instances in order to select a target agent. This avoids the expensive bidding process. The scheme is implemented in a simulated distributed hospital system where the CNP is used for resource sharing across hospitals. Experimental results demonstrate that with the incorporation of the IBL, the system performance improves significantly. The system is better scalable with respect to the number of tasks.
3086074
An Exercise in Fault-Containment: Self-Stabilizing Leader Election
Self-stabilizing algorithms are designed to guarantee convergence to some desired stable state from arbitrary initial states arising out of an arbitrarily large number of faults. However, in a well-designed system, the simultaneous occurrence of a large number of faults is rare. It is therefore desirable to design algorithms that are not only self-stabilizing, but also have the ability to recover very fast from a bounded number of faults. As an illustration, we present a simple self-stabilizing leader election protocol that recovers in O(1) time from a state with a single transient fault on oriented rings. Only the faulty node and its two neighbors change their state during convergence to a stable state. Thus, the effect of a single fault is tightly contained around the fault. The technique for transforming a self-stabilizing algorithm into its fault-contained version is simple and general, and can be applied to other problems as well that satisfy certain properties.
1019520
Vertex Partitioning Problems On Partial k-Trees
We describe a general approach to obtain polynomial-time algorithms over partial k-trees for graph problems in which the vertex set is to be partitioned in some way. We encode these problems with formulae of the Extended Monadic Second-order (or EMS) logic. Such a formula can be translated into a polynomial-time algorithm automatically. We focus on the problem of partitioning a partial k-tree into induced subgraphs isomorphic to a fixed pattern graph; a distinct algorithm is derived for each pattern graph and each value of k. We use a “pumping lemma” to show that (for some pattern graphs) this problem cannot be encoded in the “ordinary” Monadic Second-order logic—from which a linear-time algorithm over partial k-trees would be obtained. Hence, an EMS formula is in some sense the strongest possible. As a further application of our general approach, we derive a polynomial-time algorithm to determine the maximum number of co-dominating sets into which the vertices of a partial k-tree can be partitioned. (A co-dominating set of a graph is a dominating set of its complement graph).
5331854
On the Scalable Computation of Large Sets of Integrals
We consider efficient strategies for the parallel and distributed computation of large sets of multivariate integrals. These arise in many applications such as computational chemistry, high energy physics and finite element problems. We use a hierarchical architecture which is highly scalable and allows parallelization not only at the domain level but also at the integral level. We present experimental results on a family of parametrized integrals and show that our approach leads to an efficient scalable load balanced algorithm. The methods are easily applicable to other areas where a large number of problems need to be solved efficiently on a parallel and distributed system.
38885821
Embeddings of k-Connected Graphs of Pathwidth k
We present O(n3) embedding algorithms (generalizing subgraph isomorphism) for classes of graphs of bounded pathwidth, where n is the number of vertices in the graph. These include the first polynomialtime algorithm for minor containment and the first O(nc) algorithm (c a constant independent of k) for topological embedding of graphs from subclasses of partial k-trees. Of independent interest are structural properties of k-connected graphs of bounded pathwidth on which our algorithms are based. We also describe special cases which reduce to various generalizations of string matching, permitting more efficient solutions.
193663
SAT-Based Image Computation with Application in Reachability Analysis
Image computation nds wide application in VLSI CAD, such as state reachability analysis in formal veri cation and synthesis, combinational veri cation, combinational and sequential test. Existing BDD-based symbolic algorithms for image computation are limited by memory resources in practice, while SAT-based algorithms that can obtain the image by enumerating satisfying assignments to a CNF representation of the Boolean relation are potentially limited by time resources. We propose new algorithms that combine BDDs and SAT in order to exploit their complementary bene ts, and to o er a mechanism for trading o space vs. time. In particular, (1) our integrated algorithm uses BDDs to represent the input and image sets, and a CNF formula to represent the Boolean relation, (2) a fundamental enhancement called BDD Bounding is used whereby the SAT solver uses the BDDs for the input set and the dynamically changing image set to prune the search space of all solutions, (3) BDDs are used to compute all solutions below intermediate points in the SAT decision tree, (4) a ne-grained variable quanti cation schedule is used for each BDD subproblem, based on the CNF representation of the Boolean relation. These enhancements coupled with more engineering heuristics lead to an overall algorithm that can potentially handle larger problems. This is supported by our preliminary results on exact reachability analysis of ISCAS benchmark circuits.
12588315
The Many Faces of Process Interaction Graphs: A Data Management Perspective
WE USE THE EXPRESSION “process interaction graph” (PIG) as a general purpose term to cover instances of network-like structures with specific semantics, including signal transduction networks, gene regulatory networks, metabolic pathways and so forth, because we believe that despite the differences in biological significance, they can be treated in a uniform data management framework. Aside from the fact that they are all graph-like entities, PIGs share a few common characteristics, such as follows: