4 research outputs found

    Literature Survey on Employee Activity Tracking Tool in an Intranet based System for Security and Performance Evaluation

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    In the digital world aided by Networked Computers, it is a daunting task toenforce security measures, especially when the data is potentially confidential to the firm at hand. With high efficiency systems in place, like firewalls and honey pots, to negate any attack over the network, the perpetrators now concentrate on breaking the weaker links in any organization, the employees. For an enterprise it is very important for employer to have a performance evaluation of his employees and to detect insider attacks and to keep company's data safe and prevent leaking of the companies secure data. An employee activity tool is a tool which allows an employer to track the activities of an employee in his working environment. The employee activity tool is based on remote administration concept. This tool will have a platform on which various plug-in can be written. The employee activity tracking tool will be multiplatform. The loss of productivity and intellectual theft are major concerns in any organization. In this paper we have studied various operations to be performed needed to be performed to enforce security measures against insider attack and to track and increase employee?s productivity

    Adaptive Quality of Service Control for MQTT-SN

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    Internet of Things and wireless sensor networks applications are becoming more and more popular nowadays, supported by new communication technologies and protocols tailored to their specific requirements. This paper focuses on improving the performance of a Wireless Sensor Network operated by the MQTT-SN protocol, one of the most popular publish/subscribe protocols for IoT applications. In particular, we propose a dynamic Quality of Service (QoS) controller for the MQTT-SN protocol, capable of evaluating the status of the underlying network in terms of end-to-end delay and packet error rate, reacting consequently by assigning to a node the best QoS value. We design and implement the QoS controller in a simulated environment based on the ns-3 network emulator and we perform extensive experiments to prove its effectiveness compared to a non-controlled scenario. The reported results show that, by controlling the Quality of Service, it is possible to manage effectively the number of packets successfully received by each device and their average latency, to improve the quality of the communication of each end node

    Implementation and Analysis of Communication Protocols in Internet of Things

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    Internet of Things (IoT) is the future of all the present-day devices around the globe. Giving them internet connectivity makes IoT the next frontier of technology. Possibilities are limitless as the devices communicate and interact with each other which make it even more interesting for the global markets. For example, Rolls-Royce announced that it would use the Microsoft Azure IoT suite and also the Intelligence suite of Cortana to keep track of the fuel usage, for performance analysis, to optimize the fly routes etc. which improves the airline efficiency. The devices must communicate with each other, the data from these devices must be collected by the servers, and the data is then analyzed or provided to the people. For all this to happen, there is a need for efficient protocols to ensure that the communication is secure and to avoid loss of data. This research is about the implementation and analysis of various protocols that can be used for the communication in IoT. Various protocols with various capabilities are required for different environments. The internet today supports hundreds of protocols from which choosing the best would be a great challenge. But each protocol is different in its own way when we have the specifics like security, reliability, range of communication etc. This research emphasizes on the best available protocols and the environments that suit them the most. It provides an implementation of some of the protocols and analyzes the protocols according to the results obtained. The data collected from the sensors/devices through a protocol is also subject to predictive analysis which improves the scope of the project to performing data analysis on the data collected through IoT

    A self-healing framework for WSNs : detection and recovery of faulty sensor nodes and unreliable wireless links

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    Proponemos un marco conceptual para acoplar t茅cnicas de auto-organizaci贸n y t茅cnicas de autocuraci贸n. A este marco se le llama de auto-curaci贸n y es capaz de hacer frente a enlaces inal谩mbricos inestables y nodos defectuosos. Dividimos el marco en dos componentes principales: la auto-organizaci贸n y auto-curaci贸n. En el componente de auto-organizaci贸n, nosotros construimos una topolog铆a de 谩rbol que determine las rutas hacia el sumidero. En el componente de auto-curaci贸n, la topolog铆a del 谩rbol se adapta a ambos tipos de fallas siguiendo tres pasos: recopilaci贸n de informaci贸n, detecci贸n de fallas, y la recuperaci贸n de fallos. En el paso de recopilaci贸n de informaci贸n, los nodos determinan el estado actual de la red mediante la recopilaci贸n de informaci贸n de la capa MAC. En el paso de detecci贸n de fallas, los nodos analizan la informaci贸n recopilada y detectan nodos/enlaces defectuosos. En el paso de recuperaci贸n de fallos, los nodos recuperan la topolog铆a del 谩rbol mediante la sustituci贸n de componentes defectuosos con redundantes (es decir, componentes de respaldo). Este marco permite una red con resiliencia que se recupera sin agotar los recursos de la red.We propose a conceptual framework for putting together self-organizing and self-healing techniques. This framework is called the self-healing framework and it is capable of coping with unstable wireless links and faulty nodes. We divide the framework into two major components: selforganization and self-healing. In the self-organization component, we build a tree topology that determines routing paths towards the sink. In the self-healing component, the tree topology copes with both types of failures by following three steps: information collection, fault detection, and fault recovery. In the information collection step, the nodes determine the current status of the network by gathering information from the MAC layer. In the fault detection step, the nodes analyze the collected information and detect faulty nodes/links. In the fault recovery step, the nodes recover the tree topology by replacing the faulty components with redundant ones (i.e., backup components). This framework allows a resilient network that recovers itself without depleting the network resources.Doctor en Ingenier铆aDoctorad
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