Remote Patient Identification based on ECG and Heart Beat Pattern over Wireless Channel

Wireless Body Area Network (WBAN) is an innovative solution for distant monitoring of patients. In WBAN sensors are placed on human body to monitor vital parameters, and these parameters send to physician using wireless network. As in wireless network data is aggregated before transmission therefore when data is de-aggregated on receiver side it is important to know which data belongs to particular patient. In this work, it is shown that electrocardiogram (ECG) and heart beat pattern itself can be used for the identification of patient as it carries distinctive features which are unique to each person. Moreover, ECG is an image thus when transferred over Orthogonal Frequency Division Multiplexing (OFDM) wireless channel adds noise, therefore a level of Signal-to-Noise Ratio (SNR) needs to be maintained for error free recovery. This paper proposes ECG and heart beat pattern based patient identification process over OFDM channel. Proposed methodology is tested on ECG database and it has been found that the accuracy of the method is 99.98%

FACES: friend-based ad hoc routing using challenges to establish security in MANETs systems

Friend based Ad hoc routing using Challenges to Establish Security (FACES) is an algorithm to provide secure routing in ad hoc mobile networks. We propose this scheme that has been drawn from a network of friends in real life scenarios. The algorithm works by sending challenges and sharing friend Lists to provide a list of trusted nodes to the source node through which data transmission finally takes place. The nodes in the friend list are rated on the basis of the amount of data transmission they accomplish and their friendship with other nodes in the network. The account of friendship of a node with other nodes in the network is obtained through the Share Your Friends process which is a periodic event in the network. As a result of this scheme of operation, the network is able to effectively isolate the malicious nodes which are left with no role to play in the ad hoc network. One major benefit of this scheme is that the nodes do not need to promiscuously listen to the traffic passing through their neighbors. The information about the malicious nodes is gathered effectively by using Challenges. This reduces the overhead on the network significantly. Through extensive simulation analysis it was inferred that this scheme provides an efficient approach towards security and easier detection of malicious nodes in the mobile ad hoc network

A Convergent Algorithm for Energy-Balanced Cluster-Heads Selection in Wireless Sensor Networks

Due to the limited energy of sensor nodes, it is a research goal that the lifetime of sensor networks is prolonged by transmitting the sensed data to the base station in an energy-saving way. Previous algorithms aim at reducing the average energy consumption rate to extend the network lifetime. However, some nodes sometimes may be served as the cluster-head too many times to conserve their energy, resulting in reduced network lifetime. Thus, the large deviation of network lifetime makes these algorithms impractical. This paper proposes a new clustering algorithm which not only reduces the average energy consumption rate, but also converges the residual energies of all nodes on a small interval. Based on the two-region cluster-heads selection mechanism, the coordinator adaptively adjusts the far-near regions to converge the energies of all nodes on a small interval. With the exclusion-circle of cluster-heads, cluster-heads can be distributed evenly in a spatial respect for each round, resulting in reduced energy consumption. The simulation results show that the proposed algorithm not only makes cluster-heads distribute evenly in a spatial respect but also converges the residual energies of all nodes on a small interval, resulting in extending the network lifetime significantly and stably