Prasan Kumar Sahoo

Efficient Security Mechanisms for mHealth Applications Using Wireless Body Sensor Networks

Recent technological advances in wireless communications and physiological sensing allow miniature, lightweight, ultra-low power, intelligent monitoring devices, which can be integrated into a Wireless Body Sensor Network (WBSN) for health monitoring. Physiological signals of humans such as heartbeats, temperature and pulse can be monitored from a distant location using tiny biomedical wireless sensors. Hence, it is highly essential to combine the ubiquitous computing with mobile health technology using wireless sensors and smart phones to monitor the well-being of chronic patients such as cardiac, Parkinson and epilepsy patients. Since physiological data of a patient are highly sensitive, maintaining its confidentiality is highly essential. Hence, security is a vital research issue in mobile health (mHealth) applications, especially if a patient has an embarrassing disease. In this paper a three tier security architecture for the mHealth application is proposed, in which light weight data confidentiality and authentication protocols are proposed to maintain the privacy of a patient. Moreover, considering the energy and hardware constraints of the wireless body sensors, low complexity data confidential and authentication schemes are designed. Performance evaluation of the proposed architecture shows that they can satisfy the energy and hardware limitations of the sensors and still can maintain the secure fabrics of the wireless body sensor networks. Besides, the proposed schemes can outperform in terms of energy consumption, memory usage and computation time over standard key establishment security scheme.

Computational geometry based distributed coverage hole detection protocol for the wireless sensor networks

In wireless sensor networks, the purpose of surveillance cannot be fulfilled if coverage holes are generated due to accidental death of the nodes caused due to technical failures, explosions and malicious activities or power exhaustion. Since, sensors are normally deployed randomly over the dense forests and harsh terrains, it is not possible to find out the coverage holes manually. Hence, in this work a computational geometry approach based distributed hole detection protocol is designed to find out the coverage holes in a post deployment scenario. An efficient geometric method with proper theoretical basis is used to detect the coverage holes of the wireless sensor network, where communication and sensing range of the nodes are same. Performance evaluation of our protocol shows that the hole detection time and energy consumption due to hole detection outperforms over similar hole detection protocols.

HORA: A Distributed Coverage Hole Repair Algorithm for Wireless Sensor Networks

In wireless sensor networks, random deployment of nodes may cause serious coverage overlapping among the nodes and the original network may suffer severe coverage problems due to death of the nodes after deployment. In this paper, efficient distributed coverage hole repair algorithms are proposed taking density of the nodes in the post deployment scenario. The proposed algorithms consider limited mobility of the nodes and can select the mobile nodes based on their degree of coverage overlapping. In order to repair coverage holes of the network, nodes with higher degree of density are moved to maintain uniform network density without increasing the coverage degree of the neighbors of a mobile node. Simulation results show that the energy consumption due to mobility of nodes is least as compared to other similar protocols of the Wireless Sensor Networks. Besides, it is observed that substantial amount of coverage overlapping can be minimized and percentage of coverage of the holes can be maximized.

Target tracking and boundary node selection algorithms of wireless sensor networks for internet services

Wireless sensor network (WSN) is an integral part of Internet of Things (IoT), in which sensors can be used to keep track with interesting targets under surveillance. Target tracking is one of the important research issues, where sensors are deployed in many applications such as campus security, surveillance, habitat and battle field monitoring. Information can be forwarded in an ad hoc multi-hop fashion via internet to monitor a specific region and can form a ubiquitous network for several internet services. In this paper, Sequential Boundary Node Selection (SBNS) and Distributed Boundary Node Selection (DBNS) algorithms are proposed to find out the boundary nodes of the wireless sensor network. Besides, a target tracking protocol is proposed to detect the entry and exit of the targets using those boundary nodes. Simulation results show that the selection of boundary nodes in our protocol is almost close to the optimal one and the time of selecting boundary nodes would not increase rapidly, with increase in the size of the deployed nodes.

An Efficient Distributed Coverage Hole Detection Protocol for Wireless Sensor Networks

In wireless sensor networks (WSNs), certain areas of the monitoring region may have coverage holes and serious coverage overlapping due to the random deployment of sensors. The failure of electronic components, software bugs and destructive agents could lead to the random death of the nodes. Sensors may be dead due to exhaustion of battery power, which may cause the network to be uncovered and disconnected. Based on the deployment nature of the nodes in remote or hostile environments, such as a battlefield or desert, it is impossible to recharge or replace the battery. However, the data gathered by the sensors are highly essential for the analysis, and therefore, the collaborative detection of coverage holes has strategic importance in WSNs. In this paper, distributed coverage hole detection algorithms are designed, where nodes can collaborate to detect the coverage holes autonomously. The performance evaluation of our protocols suggests that our protocols outperform in terms of hole detection time, limited power consumption and control packet overhead to detect holes as compared to other similar protocols.

Big data analytic architecture for intruder detection in heterogeneous wireless sensor networks

Barrier coverage in Wireless Sensor Networks (WSNs) is an important research issue as intruder detection is the main purpose of deploying wireless sensors over a specified monitoring region. In WSNs, excessive volume and variety of sensor data are generated, which need to be analyzed for accurate measurement of the image in terms of width and resolution. In this paper, a three layered big data analytic architecture is designed to analyze the data generated during the construction of the barrier and detection of the intruder using camera sensors. Besides, a cloud layer is designed for storing the analyzed data to study the behavior of the intruder. In order to minimize the number of camera sensors for constructing the barrier, algorithms are designed to construct the single barrier with limited node mobility and the barrier path Quality of Sensing (QoS) is maintained with a minimum number of camera sensors. Simulation results show that our algorithms can construct 100% of the barrier with fewer number of camera sensors and average data processing time can be reduced by using parallel servers even if for larger size of data.

Analyzing Healthcare Big Data With Prediction for Future Health Condition

In healthcare management, a large volume of multi-structured patient data is generated from the clinical reports, doctor’s notes, and wearable body sensors. The analysis of healthcare parameters and the prediction of the subsequent future health conditions are still in the informative stage. A cloud-enabled big data analytic platform is the best way to analyze the structured and unstructured data generated from healthcare management systems. In this paper, a probabilistic data collection mechanism is designed and the correlation analysis of those collected data is performed. Finally, a stochastic prediction model is designed to foresee the future health condition of the most correlated patients based on their current health status. Performance evaluation of the proposed protocols is realized through extensive simulations in the cloud environment, which gives about 98% accuracy of prediction, and maintains 90% of CPU and bandwidth utilization to reduce the analysis time.

A Novel IEEE 802.15.4e DSME MAC for Wireless Sensor Networks

IEEE 802.15.4e standard proposes Deterministic and Synchronous Multichannel Extension (DSME) mode for wireless sensor networks (WSNs) to support industrial, commercial and health care applications. In this paper, a new channel access scheme and beacon scheduling schemes are designed for the IEEE 802.15.4e enabled WSNs in star topology to reduce the network discovery time and energy consumption. In addition, a new dynamic guaranteed retransmission slot allocation scheme is designed for devices with the failure Guaranteed Time Slot (GTS) transmission to reduce the retransmission delay. To evaluate our schemes, analytical models are designed to analyze the performance of WSNs in terms of reliability, delay, throughput and energy consumption. Our schemes are validated with simulation and analytical results and are observed that simulation results well match with the analytical one. The evaluated results of our designed schemes can improve the reliability, throughput, delay, and energy consumptions significantly.

Design and implementation of a novel service management framework for IoT devices in cloud

A service management platform for the IoT devices in Cloud is designed.Proposed Cloud platform can serve the real and non-real time data efficiently.The framework can provide services to maximum number of Application handlers.Docker container for virtualization is implemented to provide Software as a Service. With advent of new technologies, we are surrounded by several tiny but powerful mobile devices through which we can communicate with the outside world to store and retrieve data from the Cloud. These devices are considered as smart objects as they can sense the medium, collect data, interact with nearby smart objects, and transmit data to the cloud for processing and storage through internet. Internet of Things (IoT) create an environment for smart home, health care and smart business decisions by transmitting data through internet. Cloud computing, on the other hand leverages the capability of IoT by providing computation and storage power to each smart object. Researches and developers combine the cloud computing environment with that of IoT to reduce the transmission and processing cost in the cloud and to provide better services for processing and storing the realtime data generated from those IoT devices. In this paper, a novel framework is designed for the Cloud to manage the realtime IoT data and scientific non-IoT data. In order to demonstrate the services in Cloud, real experimental result of implementing the Docker container for virtualization is introduced to provide Software as a Service (SaaS) in a hybrid cloud environment.

SVANET: A Smart Vehicular Ad Hoc Network for Efficient Data Transmission with Wireless Sensors

Wireless sensors can sense any event, such as accidents, as well as icy roads, and can forward the rescue/warning messages through intermediate vehicles for any necessary help. In this paper, we propose a smart vehicular ad hoc network (SVANET) architecture that uses wireless sensors to detect events and vehicles to transmit the safety and non-safety messages efficiently by using different service channels and one control channel with different priorities. We have developed a data transmission protocol for the vehicles in the highway, in which data can be forwarded with the help of vehicles if they are connected with each other or data can be forwarded with the help of nearby wireless sensors. Our data transmission protocol is designed to increase the driving safety, to prevent accidents and to utilize channels efficiently by adjusting the control and service channel time intervals dynamically. Besides, our protocol can transmit information to vehicles in advance, so that drivers can decide an alternate route in case of traffic congestion. For various data sharing, we design a method that can select a few leader nodes among vehicles running along a highway to broadcast data efficiently. Simulation results show that our protocol can outperform the existing standard in terms of the end to end packet delivery ratio and latency.