Wireless sensor networks (WSN) allude to gathering of spatially fragmented and committed sensors for observing and documenting various physical and climatic variables like temperature, moistness and, so on. WSN is quickly growing its work in different fields like clinical, enterprises, climate following and so on. However, the sensor nodes have restricted battery life and substitution or re-energizing of these batteries in the sensor nodes is exceptionally troublesome for the most parts. Energy effectiveness is the significant worry in the remote sensor networks as it is significant for keeping up its activity. In this paper, clustering algorithms based on sensor module energy states to strengthen the network longevity of wireless sensor networks is proposed (i.e. modified MPCT algorithm) in which cluster head determination depends on the every cluster power centroid as well as power of the sensor nodes. Correspondence between cluster leader and sink module employ a parameter distance edge for lessening energy utilization. The outcome got shows a normal increment of 60% in network lifetime compared to Low energy adaptive protocol, Energy efficient midpoint initialization algorithm (EECPK-means), Park K-means algorithm and Mobility path selection protocol.

Enhancement of Energy Efficiency and Network Lifetime Using Modified MPCT Algorithm in Wireless Sensor Networks

In wireless sensor networks (WSNs), the sensed data by sensors need to be gathered, so that one very important application is periodical data collection. There is much effort which aimed at the data collection scheduling algorithm development to minimize the latency. Most of previous works investigating the minimum latency of data collection issue have an ideal assumption that the network is a centralized system , in which the entire network is completely synchronized with full knowledge of components. In addition, most of existing works often assume that any (or no) data in the network are allowed to be aggregated into one packet and the network models are often treated as tree structures. However, in practical, WSNs are more likely to be distributed systems , since each sensor’s knowledge is disjointed to each other, and a fixed number of data are allowed to be aggregated into one packet. This is a formidable motivation for us to investigate the problem of minimum latency for the data aggregation without data collision in the distributed WSNs when the sensors are considered to be assigned the channels and the data are compressed with a flexible aggregation ratio, termed the minimum-latency collision-avoidance multiple-data-aggregation scheduling with multi-channel (MLCAMDAS-MC) problem. A new distributed algorithm, termed the distributed collision-avoidance scheduling (DCAS) algorithm, is proposed to address the MLCAMDAS-MC. Finally, we provide the theoretical analyses of DCAS and conduct extensive simulations to demonstrate the performance of DCAS.

Challenges, Designs, and Performances of a Distributed Algorithm for Minimum-Latency of Data-Aggregation in Multi-Channel WSNs

Wireless Rechargeable Sensor Networks (WRSNs) are emerging systems to build data acquisition systems to monitor critical areas. It has better features than Wireless Sensor Networks (WSNs) since in WRSNs, sensors are rechargeable. Wireless Rechargeable Sensor Networks allow sensors with sensing ability to collect and supply data to the operation center (sink). The Wireless Rechargeable Sensor Network appears as a more advanced solution because it can overcome the challenges and disadvantages such as battery limitation. In practical Wireless Rechargeable Sensor Networks, there is a budgetary constraint for the different expenditure categories, and therefore the number of used mobile chargers needs to be minimized. We investigate the problem of scheduling the minimum number of mobile chargers to replenish energy all sensors in a WRSN such that the network can be operated without limitations, and the total number of used chargers is minimized, referred to as the Periodic Energy Replenishment with Minimum Mobile Charger (PERMMC) problem. We design a new algorithm, namely the Mobile Charger Scheduling Algorithm (MCSA) to address the PERMMC problem. Finally, we conduct extensive simulations and provide analyses to demonstrate the performance of MCSA.

WRSNs: Toward an Efficient Scheduling for Mobile Chargers

Cloud computing is an important technology to offer consumer appliances a wide pool of elastic resources. The heterogeneous network faces collision while making communication, which reduces the entire network performance. The future cloud-edge networks will deal with a vast amount of clients and servers, such as the Internet of Things (IoT) and the 6G networks, which require flexible solutions. From these points, Multiple Machine Access Learning with Collision Carrier Avoidance (MMALCCA) protocol is proposed in the environment of 6G Internet of Things for creating an effective communication process. This protocol employs the Media Access Control (MAC) protocol for the sync of high-speed wireless communication networks in the Terahertz (THz) band. MMALCCA performs multiple machine access and collision control for improving the resource utilization and latency-less services of the users. The decisions of the protocol are made using the output of the classification and regression learning method for improving the efficiency of MAC sync. The performance of the proposed protocol is verified using the metrics latency, collision probability, service failure, and resource utilization by varying channels and user equipment density.

Creating Collision-Free Communication in IoT with 6G Using Multiple Machine Access Learning Collision Avoidance Protocol

EDGF: Empirical dataset generation framework for wireless sensor networks

Data collection is one of the most important operations in applications of wireless sensor networks (WSNs). In many emerging WSN applications, it is urgent to achieve a guarantee for the latency involved in collecting data. Many researchers have studied collecting data in WSNs with minimum latency but without data collision while assuming that any (or no) data are allowed to be aggregated into one packet. In addition, tree structures are often used for solutions. However, in some cases, a fixed number of data are allowed to be aggregated into one packet. This motivates us to study the problem of minimizing the latency for data aggregation without data collision in WSNs when a fixed number of data are allowed to be aggregated into one packet, termed the minimum-latency collision-avoidance multiple-data-aggregation scheduling (MLCAMDAS) problem. The MLCAMDAS problem is shown to be NP-complete here. In addition, a nontree-based method, termed the independent-set-based collision-avoidance scheduling (ISBCAS) algorithm, is proposed accordingly. The ISBCAS is demonstrated via simulations to have good performance.

Ting-Yan Liou

Papers

An Efficient Minimum-Latency Collision-Free Scheduling Algorithm for Data Aggregation in Wireless Sensor Networks