Several routing schemes in ad hoc networks first establish a virtual backbone and then route messages via back-bone nodes. One common way of constructing such a backbone is based on the construction of a minimum connected dominating set (CDS). In this paper we present a very simple distributed algorithm for computing a small CDS. Our algorithm has an approximation factor of at most 6.91, improving upon the previous best known approximation factor of 8 due to Wan et al. [INFOCOM'02], The improvement relies on a refined analysis of the relationship between the size of a maximal independent set and a minimum CDS in a unit disk graph. This subresult also implies improved approximation factors for many existing algorithm.

A Simple Improved Distributed Algorithm for Minimum CDS in Unit Disk Graphs

We consider graph coloring and related problems in the distributed message-passing model. \em Locally-iterative algorithms are especially important in this setting. These are algorithms in which each vertex decides about its next color only as a function of the current colors in its 1 - hop-neighborhood. In STOC'93 Szegedy and Vishwanathan showed that any locally-iterative (Δ + 1)-coloring algorithm requires Ω(Δ log Δ + log^* n) rounds, unless there exists "a very special type of coloring that can be very efficiently reduced" \citeSV93. No such special coloring has been found since then. This led researchers to believe that Szegedy-Vishwanathan barrier is an inherent limitation for locally-iterative algorithms, and to explore other approaches to the coloring problem \citeBE09,K09,B15,FHK16. The latter gave rise to faster algorithms, but their heavy machinery which is of non-locally-iterative nature made them far less suitable to various settings. In this paper we obtain the aforementioned special type of coloring. Specifically, we devise a locally-iterative (Δ + 1)-coloring algorithm with running time O(Δ + log^* n), i.e., \em below Szegedy-Vishwanathan barrier. This demonstrates that this barrier is not an inherent limitation for locally-iterative algorithms. As a result, we also achieve significant improvements for dynamic, self-stabilizing and bandwidth-restricted settings. This includes the following results. \beginitemize item We obtain self-stabilizing distributed algorithms for (Δ + 1)-vertex-coloring, (2Δ - 1)-edge-coloring, maximal independent set and maximal matching with O(Δ + log^* n) time. This significantly improves previously-known results that have O(n) or larger running times \citeGK10. item We devise a (2Δ - 1)-edge-coloring algorithm in the CONGEST model with O(Δ + log^* n) time and O(Δ)-edge-coloring in the Bit-Round model with O(Δ + log n) time. The factors of log^* n and log n are unavoidable in the CONGEST and Bit-Round models, respectively. Previously-known algorithms had superlinear dependency on Δ for (2Δ - 1)-edge-coloring in these models. item We obtain an arbdefective coloring algorithm with running time O(\sqrt Δ + log^* n). Such a coloring is not necessarily proper, but has certain helpful properties. We employ it in order to compute a proper (1 + e)Δ-coloring within O(√ Δ + log^* n) time, and √(Δ + 1)√-coloring within √O(√ Δ log Δ log^* Δ + log^* n)√ time. This improves the recent state-of-the-art bounds of Barenboim from PODC'15 \citeB15 and Fraigniaud et al. from FOCS'16 \citeFHK16 by polylogarithmic factors. item Our algorithms are applicable to the SET-LOCAL model \citeHKMS15 (also known as the weak LOCAL model). In this model a relatively strong lower bound of √Ω(Δ^1/3 )√ is known for √(Δ + 1)√-coloring. However, most of the coloring algorithms do not work in this model. (In \citeHKMS15 only Linial's √O(Δ^2)√-time algorithm and Kuhn-Wattenhofer √O(Δ log Δ)√-time algorithms are shown to work in it.) We obtain the first linear-in-Δ algorithms that work also in this model. \enditemize

Locally-Iterative Distributed (Δ+ 1): -Coloring below Szegedy-Vishwanathan Barrier, and Applications to Self-Stabilization and to Restricted-Bandwidth Models

In Wireless Sensor Networks (WSNs) keeping the network connectivity is a challenging task because failure in some nodes may cut off the communication paths between other nodes. A k-connected network remains connected after failure in any k-1 nodes, hence we can consider the k value as a metric for measuring the connectivity robustness of WSNs. In this paper we consider the effect of random node distribution and transmission range of nodes on k value of WSNs. To evaluate the effect of node count and transmission range on k, we generated 1000 random topologies with different transmission range and node count and measured the k value of established networks. Our simulation result showed that in a field of 1000 × 1000 m2 area, with unified random distribution we need at least 200 nodes with minimum transmission range 80 m to expect a network with k ≥ 1. Also, the simulation results showed that random distributing of up to 500 nodes with transmission range lower than 80 in a field with mentioned area, generally leads to disconnected networks.

The Effect of Random Node Distribution and Transmission Ranges on Connectivity Robustness in Wireless Sensor Networks

Distributed Wireless Sensor Networks (DWSNs) comprised of set of sensor nodes that are geographically distributed in harsh environments. However, a centralized WSN does not consider the network scalability and also leads to high energy consumption. Due to these open issues, distributed computing approach is considered since it resolves scalability issue and several paths are established for data transmission. To achieve higher energy efficiency, scalability and security, in this paper we propose a distributed protocol called Secure Coronas-Based Zone Clustering and Routing (SC-ZCR). The proposed SC-ZCR aim at addressing the number of issues in DWSN and it support for long-term deployment. In SC-ZCR, we will pursue several processes including Zone Clustering, Energy Efficient Routing and Data Encryption and Security Verification. Zone clustering is carried out using Adaptive Neuro-Fuzzy System, where we consider four parameters: node angle, distance between sensor node to the sink node, node residual energy and belief value. Belief value of each sensor node is computed using Principal Component Analysis. Then energy efficient routing is established by Q-Hop Routing Protocol, which finds optimum and shortest path using Whale Optimization Algorithm. For data packets encryption, RC6 is used and then security level of data packets are verified using potential weight factor $$\delta$$, which is computed using key size $$K$$, block size $$B$$, and number of rounds $$R$$. Experiments conducted using NS3.26 simulator and the simulation result show that the proposed SC-ZCR outperforms in terms of Coverage Ratio, Residual Energy, Network Lifetime, Delay, Packet Drop Rate, and Security Strength.

Secure Coronas Based Zone Clustering and Routing Model for Distributed Wireless Sensor Networks

Wireless sensor networks play an important role in daily life and have been applied in diverse fields. In practice, malware tries to infect sensor nodes, while wireless sensor network prevents from...

https://journals.sagepub.com/doi/pdf/10.1177/1550147719841293

An attack-defense game based reliability analysis approach for wireless sensor networks:

An energy-efficient, self-stabilizing and distributed algorithm for maximal independent set construction in wireless sensor networks

A fault-tolerant and distributed capacitated connected dominating set algorithm for wireless sensor networks

Maximal independent set (MIS) has significantly important in practical applications for wireless sensor networks (WSNs). A distributed self-stabilizing system can initially start at any illegal state and takes back a legal state as long as there is no external intervention. We propose a novel distributed self-stabilizing MIS algorithm using two-hop information. It stabilizes an unstable system at most n-1 moves under an unfair distributed scheduler where n is the number of nodes in the graph. We use the message passing model as the communication model where this model is very appropriate for WSNs. The communication consumes the most energy in WSNs. So, move count is at least as important as round count where reducing the move count prolongs the lifetime of the network. We analyzed theoretically and tested it on SimPy discrete event simulator on randomly generated connected simple undirected graphs to compare with its counterparts in terms of transmitted bit count and move count against various node degrees and node counts.

An Asynchronous Self-Stabilizing Maximal Independent Set Algorithm in Wireless Sensor Networks Using Two-Hop Information

Connectivity stability is one of the most important requirements in Wireless Sensor Networks (WSNs) that has a considerable effect on the functionality of these networks. WSNs use multi hop connections for packet delivery. Failures on nodes may change the network topology and connectivity status. A reliable WSN must tolerate the node failures without loosing its connectivity. One of an important approach for increasing the network connectivity is k-connectivity. A k-connected network remains connected after removing arbitrary k-1 nodes. So, in high k values, the connectivity of a WSN can be considered as stable. Finding the k value of a WSN provides useful information about the stability of its connections. In this paper, we propose a distributed algorithm for estimating the k value of a WSN. The proposed approach establishes distributed depth first search (DFS) trees to find the available disjoint paths between the nodes. The minimum number of disjoint paths between the nodes determines the k value. During the DFS tree construction, the nodes overhear the sent packets of their neighbors to reduce the total energy consumption. The comprehensive simulation results show that the mean square errors of the estimated values by the proposed algorithm reach up to 28.5% lower and its correct estimations are up to 32% higher than the existing distributed algorithms.

A Depth-First Search based Connectivity Estimation Approach for Fault Tolerant Wireless Sensor Networks

A self-stabilizing distributed system can initially start at any state and regain a legal state in a finite time without any external intervention. Self-stabilizing systems can automatically recover from faults and they are popular fault tolerant systems. Simulating self-stabilizing systems is a vital task in case of fault-tolerant distributed networks where node and edge updates can be frequent. A discrete-event simulation is a method of simulating the behavior and performance of an algorithm running on a distributed system. To the best of our knowledge, there are few simulators for self-stabilizing distributed algorithms in literature where these simulators are generally outdated and hard to use. In this paper we propose a novel distributed self-stabilizing discrete-event simulator (SELFSIM). SELFSIM is written in C# programming language on .NET Framework and supports up-to-date principles of software development techniques such as separation of concerns. We give the design and implementation of the proposed simulator and compare SELFSIM with its counterparts by considering various parameters such as supported node count (scalability), topological features, daemon (scheduler) types, etc., and show the superiority of our simulator.

Ozkan Arapoglu

Papers

An energy-efficient, self-stabilizing and distributed algorithm for maximal independent set construction in wireless sensor networks

A fault-tolerant and distributed capacitated connected dominating set algorithm for wireless sensor networks

An Asynchronous Self-Stabilizing Maximal Independent Set Algorithm in Wireless Sensor Networks Using Two-Hop Information

A Depth-First Search based Connectivity Estimation Approach for Fault Tolerant Wireless Sensor Networks

SELFSIM: A Discrete-Event Simulator for Distributed Self-Stabilizing Algorithms