Showing papers by "Mayank Dave published in 2018"

A novel fault detection and recovery technique for cluster‐based underwater wireless sensor networks

Abstract: Int J Commun Syst. 2017;e3485. https://doi.org/10.1002/dac.3485 Summary The performance of underwater wireless sensor network gets affected by the working of a cluster in the network. The cluster head (CH) or cluster member (CM) fails because of energy depletion or hardware errors that increase delay and message overhead of the network. To recover the affected cluster, a technique is required to identify the failed CH or CM. We propose a fault detection and recovery technique (FDRT) for a cluster‐based network in this paper. Primarily, while selecting the CH, a backup cluster head (BCH) is selected using fuzzy logic technique based on parameters such as node density, residual energy, load, distance to sink, and link quality. Then, failure of CH, BCH, and CM is detected. If fault is detected at CH, then the BCH will start performing the task of failed CH. Simultaneously, when BCH failed, any other CM will be elected as BCH. If any of the CM appears to be nonperforming, then CH will detect the communication failure and request BCH to transfer the data from the failed CM to CH. The comparison of proposed FDRT is performed with existing FDRTs EDETA, RCH, and SDMCGC on the basis of packet drop, end‐to‐end delay, energy consumption, and delivery ratio of data packets. By simulation results, it is shown that FDRT for cluster‐based underwater wireless sensor network results in quicker detection of failures and recovery of the network along with the reduction in energy consumption, thereby increasing the lifespan of the network.

Adaptive Error Control Technique for Cluster-Based Underwater Wireless Sensor Networks

Abstract: Underwater Wireless Sensor Networks (UWSNs) are the networks where the sensors are deployed under the water to monitor the aquatic environment. UWSNs are susceptible to adverse environmental conditions making the network prone to errors. Since the underwater environment has a fluctuating nature with respect to temperature, speed, etc., it is necessary to make the network adaptive to frequent changes. In this paper, we propose an adaptive error control technique for cluster-based UWSN. The proposed technique initially makes the cost involved in data transmission adaptive and then makes the transmission error controlled by encoding the data to be transmitted. Thus, the network operation is made efficient by handling the error issue and also by making it adaptive. Simulation results show that the proposed AECT improves the 28% packet delivery ratio by reducing the 8% packet drops, 59% delay and 57% energy consumption when compared to the existing techniques.

Securing Fog and Cloud Communication Using Attribute Based Access Control and Re-encryption

Abstract: Fog Computing is a type of distributed computing that reduces computation on the cloud by creating a new layer between the Internet of Things (IoTs) devices and the cloud. This helps to deliver the services more efficiently and effectively. The security concerns in fog computing are inherited from the cloud itself as the fog computing is derived from cloud computing. So, a major security concern in fog computing is during sharing of data, as illegitimate users could get access while the data is being shared. Attribute Based Encryption (ABE) method is proved to be beneficial for securing the data, but ABE method alone is not sufficient as there are various security concerns such as forward issue and backward issue. Various methods have been proposed by researchers to solve the problem, one such efficient solution is re-encryption. In this paper we propose a scheme that uses Ciphertext-policy Attribute based Encryption along with re-encryption for providing access control in fog and cloud communication. The analysis of the proposed scheme reveals better security and performance. We have also implemented the proposed scheme to show its effectiveness.

Deployment Based Attack Resistant Key Distribution with Non Overlapping Key Pools in WSN

Abstract: Many current key management schemes do not effectively consider the attack probability and assume it to be same for every sensor node. However, for some applications like disaster management and military surveillance, attacks on sensor nodes may occur with different probabilities. In this paper, we have proposed a deployment based attack resistant key distribution for cellular model of wireless sensor networks. The main strength of the proposed scheme lies in incorporating the concepts such as the node density of the cell, the neighbor influence factor, gradient distance, placement of the sink node and the type of application running on the nodes to construct the attack matrix of each cell of the network. The domain key pool of the cell is further extended by the sharing of adjacent sub key pools followed by the hash computation on the keys and combining the hash computed keys with the original keys. This improves the probability of connectivity and storage overhead of the proposed scheme. To improve the resilience against the node capture attack and the communication overhead, the key pool is partitioned into three non overlapping sub key pools and the keys are hashed based on the cell and the node's identifiers. It is also shown that the proposed scheme performs better in terms of the probability of connectivity and the computation overhead when compared with existing schemes.

An Efficient Traffic Management Solution in Data Center Networking Using SDN

Abstract: In today’s big data era, large scale data centers are the major infrastructure. One goal of doing research and work in the field of DCNs is to satisfy network transmission demands, increase responsiveness and throughput simultaneously. Hence, for required stable and optimized architecture an implementation based on software-defined network (SDN) is used to utilize the data center network (DCN) performance. The problem of traffic engineering is observed in the field of routing and load balancing based on traditional networks in data centers. The load balancing is a complex task due to variety in data flows. Thus various solutions have been employed in this field for better results. Load balancing shows its use in the presence of heavy flow generated during peak intervals or other occasions that ultimately results in congestion of the network and performance degradation. This paper proposed the collaboration of online routing method with multipath transmission control protocol (MPTCP) and segment routing (SR) in software defined network for batter results in DCN.

A Real-Time Application Solution in Data Center Networking Using SDN

Abstract: In this big data time today, fastness in analysis of data is highly required, so as the agility of network architecture. The aim of doing research and work in this field is to fulfill network transmission demands on time, which is considered to be a highly required factor in real time data providing scenarios. For both increasing responsiveness and high throughput there is required a stable and optimized architecture, hence more and more researchers are start moving to this new network architecture named as software-defined network (SDN). This introduces a new idea of “Programmable Network” which in turn provides flexibility, simplicity, and speeds up the network performance. The core idea behind SDN architecture is the separation of the control plane from the data plane. Thus the controller abstracts the complexity of the network. The traffic engineering problem is witnessed in the field of routing and load balancing based on traditional networks in data centers. Due to variety in data flows the load balancing in today's time is a complex task. Thus for better results various solutions have been hired. This paper proposed the collaboration of Real-time Transport Protocol (RTP) and Segment Routing (SR) for batter results in real time application data analysis in DCN using software defined network.

Key Aggregate Cryptography Based Solution for Dynamic Ownership Management in Fog Infrastructures

Abstract: Organizations across the world are using Cloud to leverage some of its key aspects, such as reduced startup costs, data transmission expenditures, pay-as-you-use model etc. Increasing usage of Cloud based services not only raises conventional issues related to data security and privacy, but also causes handling data ownership and handling it dynamically difficult. This has now become a prominent research topic. To support real-time applications, concept of Fog computing have emerged. In this paper, we propose a model utilizing Fog computing and incorporating dynamic data ownership for data aggregation and deduplication. The technique presented in the paper uses Key Aggregate Cryptography and Bilinear groups.