Peer-to-Peer Networking and Applications ( IF 4.2 ) Pub Date : 2021-05-08 , DOI: 10.1007/s12083-021-01149-8 S. Jeen Shene , W. R. Sam Emmanuel
Energy conservation is one of the major concerns in mobile cloud sensor environment, where mobile sensing devices are capable of acquiring the sensing information and send the collaborated data to cloud hosted applications. However, they are constrained by the limited computing power and the short battery life. Hence, sensor based applications need an effective scheme to collect the sensed information and offload it to the base station in an efficient manner. In this paper, an approach named Modified Partitioning Around Medoids clustering with Threshold based Cluster Head Replacement (MPAM-TCHR), is proposed that aims for better clustering and change of cluster heads for every round of data offload to reduce the energy utilization of the sensor nodes. The proposed work divides the process into four phases namely, initialization, clustering, Cluster Head (CH) formation and transmission phases. Initially, node initialization is performed, and then the modified PAM clustering algorithm accurately estimates the medoid points based on which optimal cluster set partitioning is done. Next, the four parameters namely residual energy, signal to noise ratio (SNR) of the sensors, average path loss between the node and the other nodes and the path loss between the sensor and the base station influence the CH selection. This involves a threshold based modulation measure to identify probability effective node to become CH, iteratively changing the CH at different time intervals. Ultimately, the CH offloads the collected information to the base station (BS) with low communication cost possible during a particular time interval. Experimental results show better performances in terms of metrics like network lifetime, network utilization, and the average number of alive nodes. Thus, the proposed method performs data transmission with low energy consumption and thereby able to prolong the network lifespan.
中文翻译:
移动云传感器环境中具有簇头调制的节能型改进型PAM聚类
节能是移动云传感器环境中的主要问题之一,在该环境中,移动感测设备能够获取感测信息并将协作的数据发送到云托管的应用程序。但是,它们受到计算能力有限和电池寿命短的限制。因此,基于传感器的应用需要有效的方案来收集感测到的信息并将其以有效方式卸载到基站。在本文中,提出了一种基于基于阈值的簇头替换(MPAM-TCHR)的基于类群聚类的改进分区方法(MPAM-TCHR),旨在为每轮数据卸载更好地聚类和改变簇头,以减少传感器的能源利用节点。拟议的工作将流程分为四个阶段,即初始化,聚类,群集头(CH)的形成和传输阶段。最初,执行节点初始化,然后,经过修改的PAM聚类算法会根据完成的最佳聚类集划分准确估算出类固醇点。接下来,四个参数,即剩余能量,传感器的信噪比(SNR),节点与其他节点之间的平均路径损耗以及传感器与基站之间的路径损耗会影响CH选择。这涉及基于阈值的调制度量,以识别成为CH的概率有效节点,并在不同的时间间隔上迭代地更改CH。最终,CH在特定时间间隔内以较低的通信成本将收集到的信息卸载到基站(BS)。实验结果表明,在诸如网络生存期,网络利用率和活动节点的平均数量之类的指标方面,性能更好。因此,所提出的方法以低能耗执行数据传输,从而能够延长网络寿命。