Internet of Things in Business Transformation. Группа авторов

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Internet of Things in Business Transformation - Группа авторов


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a gateway. PS has a connection to RBS directly or with multiple hops. Communication of two types, intra-WBAN and inter-WBAN occurs in the WBANs. Intra-WBAN is a communication within the sensors of a single WBAN. On the other hand, Inter-WBAN is communication among multiple WBANs. Information collected by the sensors is transmitted to the remote Medical-Server, which is situated in the hospital. Inter-WBAN communication provides dynamic access when patients are doing their normal routine work (during movement in home, office, market or playground). In this case, sensor residing on the human body may or may not be in the range of RBS. So cooperation of multiple WBANs is required for hop-to-hop communion, to reach the RBS. RBS is responsible for further transmission to Medical-Server via the internet. WBANs are capable of protecting human lives by detecting patient’s critical conditions at its early stages. Many human lives are dependent on the performance of the WBAN. Routing strategy is the key to network efficiency. There are different routing mechanisms of inter-BAN and intra-BAN communication. Each WBAN needs to be connected to the external network with the help of a gateway.

      Inter-WBAN communication can be useful in both of the cases. As WBAN consists of low power energy nodes, we required an efficient energy consumption routing technique. Clustering is one of the best solutions for efficient routing, where a cluster head is responsible for the transmission of data of multiple WBANs. Network efficiency is dependent on the cluster’s lifetime. In this paper, we proposed an optimization technique of clusters formation using Evolutionary Algorithms. Each cluster head (CH) is a gateway in between cluster members (PSs) of multiple WBANs and the external network. CHs are selected on the bases of fitness.

      A Balanced Energy Consumption (BEC) protocol is designed by [4]. In this protocol the relay node is selected with cost function which is based on distance of node form sink. To distribute load uniformly each relay node is selected for a specific round. Nodes nearer to the sink can transmit data immediately to the sink, otherwise data is passed to closest relay node. A threshold value of residual energy is also fixed on meeting the threshold value node only send critical data to sink. A simulation study has shown the better performance in term of network lifetime. Another attempt to achieve better throughput in terms of energy-consumption is achieved in heterogeneous WBAN [5]. It also works on the same principal. Residual energy, data rate and distance from sink, is the basic selection criteria for selection of relay node. Key requirement of any WBAN is minimum delay and energy efficiency. To improve the clustering in WBAN a load balancing and position adaptive technique is proposed by [6]. For the selection of cluster head the author used probability distribution method. A centralized clustering method is proposed by [7] to optimize the consumption of energy in WBAN. The cluster tree based structure is designed for the formation of uniform clusters.

      By creation of the long-lasting clusters, frequent path search is reduced. We are considering the scenario where multiple WBANs are present. Instead of having a connection of each WBAN with RBS, we considered some of the WBANs are not in the range of RBS. Each WBAN consist of one Personal Server (PS) and multiple sensor nodes. The sensor nodes pass their collected data to the PS and this PS is responsible for further transmission. In our purposed technique PS of different WBANs form clusters. Each cluster contains a cluster head and cluster members (CM) in its vicinity. CH is a selected PS of a WBAN within the WBANs of a cluster. Now all other WBANs will be connected to the CH, multiple CHs of different WBANs can have hop-to-hop communication, and this way data is passed to the nearest AP.

      Our communication can be classified into following hierarchal groups.

       Sensor node to PS

       PS(CM) to CH

       CH to RBS


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