Department of Electrical and Electronics Engineering

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Comments on An Efficient Method based on Self-Generating Disjoint Minimal Cut-Sets for Evaluating Reliability Measures of Interconnection Networks
(Totem Publisher, 2014) Chakraborty, Suparna
The recent paper published in IJPE by Tripathy et al. [1] presented a new method based on self-generating, non-redundant and disjoint cutsets to evaluate the three important reliability measures, viz., two-terminal, all-terminal and k-terminal. Authors claim that their algorithm is much more efficient as it saves the overhead of disjointing process and redundant terms removal than the existing Sum-of-Disjoint-Product (SDP) form based algorithms available in the literature. However, we observe several discrepancies in the results generated by their proposed algorithm on the considered benchmark networks and even on the illustrative example taken to describe the algorithm.
Irredundant Subset Cut Enumeration for Reliability Evaluation of Flow Networks
(IEEE, 2015-12) Chakraborty, Suparna
Capacity Related Reliability (CRR) is an important performance index for flow networks. Most of the CRR evaluation techniques proposed in literature, which deal with subset cut enumeration from minimal cut sets, generate a large number of redundant subsets. The efforts in validating these subsets as cuts and then removing the redundant subset cuts makes these approaches computationally inefficient. To solve this problem, this paper proposes a new subset cut enumeration technique using a proposed decomposition method to avoid generating higher order redundant subset cuts of the network, where order refers to the number of links present in the cut. The proposed decomposition method decomposes a cut into new cuts if the cut has a subset in already enumerated valid subset cuts. Such newly generated cuts do not have any subset which is equal to or a superset of already enumerated valid subset cuts. Therefore, if the subsets of these newly generated cuts qualify as valid subset cuts, then none of them are equal to or a superset of any earlier valid subset cuts. The subset cut enumeration technique, along with the decomposition method, completely eliminates the chances of generating higher order redundant subset cuts. However, it leaves a small chance of generating redundant subset cuts as sometimes an already enumerated valid subset cut may become a superset of a valid subset cut, enumerated from a minimal cut treated later, making previously enumerated valid subset cut(s) redundant.
Minimal Path-Based Reliability Model for Wireless Sensor Networks With Multistate Nodes
(IEEE, 2020-03) Chakraborty, Suparna
Wireless sensor networks (WSNs) find application in various fields like environmental monitoring, health-care, land security, and many more. To ease our day-to-day activity, WSNs have become an integral tool for complex data gathering tasks. Monitoring a phenomenon by a WSN depends on the collective data provided by the sensor nodes. To ensure reliable operation of WSNs, it is important to quantify the performance of such networks in terms of network reliability measures. This article studies the reliability of WSNs with multistate nodes and proposes an approach to evaluate the flow-oriented network reliability of WSNs consisting of multistate sensor nodes. The proposed method takes into account the dynamic state of the network due to multistate sensor nodes. The proposed approach includes enumeration of shortest minimal paths from application-specific flow satisfying sensor nodes (source nodes) to the sink node. It then proposes a modified sum-of-disjoint products approach to evaluate WSN reliability in the presence of multistate nodes from the enumerated shortest minimal paths. Simulations are performed on WSNs of various sizes to show the applicability of the proposed approach on arbitrary WSNs.
A Monte-Carlo Markov chain approach for coverage-area reliability of mobile wireless sensor networks with multistate nodes
(Elsevier, 2020-01) Chakraborty, Suparna
A mobile Wireless Sensor Network (mWSN) is composed of a large number of tiny, inexpensive resource-constrained sensors scattered in the field of interest, with the sink node or the data collector moving around the field. One fundamental concern of an mWSN is to provide application-specific coverage of the area under surveillance. The reliability of an mWSN depends on sensing area coverage, network connectivity, and data handling capacity of the mWSN in the presence of multi-state sensors. To mention here, each sensor node during its life cycle may exist in ACTIVE, SLEEP, RELAY, IDLE or FAIL states due to hardware failure, random duty cycle and/or energy limitations. Under such constraints, to quantify application-specific coverage oriented reliability, a new coverage-reliability index, CORE, is introduced. CORE gives a measure of the ability of a sensor network with multi-state nodes to satisfy the application-specific coverage area requirement with reliable data delivery to the mobile sink. A Monte-Carlo Markov Chain simulation approach is proposed for evaluating CORE. The conducted computational experiments are carried on mWSNs of various sizes to demonstrate the versatility of the proposed approach.
On Area Coverage Reliability of Mobile Wireless Sensor Networks With Multistate Nodes
(IEEE, 2020-05) Chakraborty, Suparna
Wireless sensor networks (WSNs) are a special type of infrastructure-less network made up of a large number of tiny sensor nodes with limited energy, processing, and communication capabilities. WSNs have applications in health care, home security, environment monitoring, etc., with research challenges in energy efficiency, network lifetime, and network reliability. One of the major research challenges lies in providing application-specific coverage of the region of interest and reliable transmission of the gathered data to the mobile sink in the presence of multi-state sensor nodes. To quantify such a capability, this paper proposes a quantitative measure, called Area Coverage Reliability (ACR) for WSNs. ACR brings together WSN reliability, area coverage, energy efficiency, mobility of data collector or sink, random duty cycle of nodes, and multi-state nature of sensor nodes under a common umbrella. This paper proposes a Monte Carlo simulation approach that utilizes an energy matrix to evaluate the effect of energy-depleted nodes and energy-oriented data transfer capability on ACR. The energy matrix reflects the residual energy of sensors, the energy required to transmit data to the neighboring nodes, connectivity, and the multi-state nature of the sensors. The proposed approach is illustrated through a series of random examples. The ACR information allows the network designers to achieve a better understanding of the impact of random duty cycle, node energy, node/link reliability, and randomly deployed sensors on reliability.
Subset Cut Enumeration of Flow Networks with Imperfect Nodes
(Totem Publisher, 2014) Chakraborty, Suparna
A general assumption made in evaluation of flow network reliability is perfectly reliable nodes. Under such assumption, network reliability is evaluated through subset cut or composite path set approaches. This paper presents a simple approach to account for node failures in reliability evaluation of flow networks using subset cut approach. The proposed approach starts with generating combinations of nodes of the network and utilizes subset cuts (with perfect nodes) to find the valid additional subset cuts due to imperfect nodes. These additional subset cuts consist of only nodes or nodes-links combinations. To illustrate efficacy of the proposed approach, computational results on various benchmarks networks are provided. The proposed method is applicable to evaluate additional minimal cut sets due to imperfect nodes from minimal cut sets (with perfect nodes) for networks considering only connectivity as the success criteria or additional subset cut set for networks with multiple node pair capacity requirements.