Abstract The revolutionary architecture termed Software‐Defined Network provides flexible network management by detaching the control logic from the underlying data plane. The flow table resides in Ternary Content Addressable Memory imparts rules for the incoming flows with a limitation of high cost, limited storage, and consumes high power. In data center networks, when the traffic rate is high the overflow occurs due to storage limitation with high packet drop, frequent rule miss, and severe controller overhead. To overcome these challenges and to provide Quality of Service to the current network design sketch‐based entry reduction scheme is proposed. It incorporates three concurrent modules integrated to function sequentially where (1) Periodical analysis in Multiple Flow Tables is performed to ensure the availability of redundant entries using the robust data mining algorithm called Term Frequency. (2) Recurrent entries are further classified and clustered using the Boyer–Moore pattern matching algorithm to facilitate the forthcoming aggregation process. (3) A compact flow table is achieved with a customized multibit trie using Huffman coding compression technique. The experimental outcomes prove that this work prevents overflow by 99.98% with 98.99% enhanced flow table space and provides a significant reduction of controller overhead than the existing schemes.

The rise of the Internet of Things has facilitated the growth of Wireless Sensor Networks (WSNs). WSN has many challenges concerning network and management. It is discovered that Software-Defined Wireless Sensor Networks (SDWSNs) could simplify WSN configuration, routing, and management. However, for obtaining a thorough view of the underlying topology, SDWSN causes many control messages to be exchanged. This consequently depletes the energy of nodes. Wherefore, solving the energy challenges of SDWSN is imperative, before they could be successfully implemented. Realizing this, we propose an architecture that adopts the control message quenching technique in the data layer devices. Based on the proposed architecture, we propose a communication protocol, Control Message Quenching-based SDWSN (CMQ-SDWSN) that facilitates a minimal exchange of control messages between the infrastructure layer and the control layer by placing entry loggers in the data layer. Furthermore, we formulated an Integer Linear Programming (ILP) problem in the control layer which enables better partitioning and distribution of rules. The simulation results show that the proposed architecture and the communication protocol reduce the control message overhead by 33.66% on average and minimize the energy consumption of nodes by 33.51% on average when compared to its counterparts.

Abstract The exponential growth in mobile broadband data traffic with demand for faster data connectivity has become the most engaging challenges for mobile operators. They are facing an enormous data load in the core network and are finding new solutions to offload data to other complementary technologies. Mobile data offloading using device-to-device (D2D) communication stands out as the promising and the low-cost solution to reduce the burden on cellular network. Data offloading is the process of reducing the load in the cellular medium by using alternative wireless technologies for bearing data using opportunistic assignment of nodes. In this paper, iNHeRENT, a Novel HybRid user equipment (UE) selection scheme using D2D communication in next generation wireless networks that provides better offloading efficiency and throughput than the existing schemes, is proposed. Here, a small set of Wi-Fi-enabled hybrid user equipment ($UE_H$*) is chosen to offload cellular data in an efficient way. The objective of the work is to use minimum number of $UE_H$* to cover maximum number of UE in the serving area of an evolved Node B and to offload maximum amount of data. A $UE_H$* is a special UE with both cellular and Wi-Fi interfaces enabled to offload data. The coverage, throughput, packet delivery ratio and offloading efficiency metrics for the selected number of $UE_H$* are considered, and it is found that an offloading efficiency of 95.45% was achieved for a minimum number of 7% $UE_H$* using iNHeRENT.

The lightening growth inInternet of Things (IoT), forced the deployment of various types of applications. Due to the likelihood of sensor failures, the applications of IoT cannot be benefited. These node failures can transform the fully‐connected network into multiple disjoint sub‐networks, named network partitioning problem where the nodes fail to perform intended services. The federation of these isolated network segments is essential. In this study, a distributed approach FRTP (Failure Recovery using Relay Nodes at Torricelli points ( )) is proposed, where the restoration of the disconnected network is initiated using the relay nodes (RNs). The performance of FRTP is evaluated using network simulator tool NS‐2 and the experimental results show that it achieves better performance than the existing approaches. The main goal of the proposed approach is to minimise the number of HRNs (Healing Relay Nodes), APL (Average path length), recovery time of the network and to maximise the average node degree. The average improvement in minimisation of number of HRN, APL, and recovery time of the network for radio range of 100 m are 21.57, 13.23, and 9.96%, respectively, and the maximisation of average node degree is 9.83%.