Clone Detection for Efficient System in WSN using AODV

Wireless sensor is wide deployed for a spread of application, starting from surroundings observance to telemedicine and objects chase, etc. For value effective sensing element placement, sensors are usually not tamperproof device and are deployed in places while not observance and protection, that creates them at risk of fully different attacks. As an example, a malicious user may compromise some sensors and acquire their private information. Then, it?ll duplicate the detectors and deploy clones in an exceedingly wireless sensor network (WSN) to launch a spread of attack that?s mentioned as clone attack. Because the duplicated sensors have an equivalent information, e.g., code and crypto graphical information, captured from legitimate sensors that may merely participate in network operation and launch attacks. Because of the low value for sensing components duplication and preparation, clone attacks became one in all the foremost essential security issues in WSNs. Thus, it?s essential to effectively detect clone attacks therefore to ensure healthy operation of WSNs

Perceptually Important Points-Based Data Aggregation Method for Wireless Sensor Networks

يستهلك إرسال واستقبال البيانات معظم الموارد في شبكات الاستشعار اللاسلكية (WSNs). تعد الطاقة التي توفرها البطارية أهم مورد يؤثر على عمر WSN في عقدة المستشعر. لذلك، نظرًا لأن عُقد المستشعر تعمل بالاعتماد على بطاريتها المحدودة ، فإن توفير الطاقة ضروري. يمكن تعريف تجميع البيانات كإجراء مطبق للقضاء على عمليات الإرسال الزائدة عن الحاجة ، ويوفر معلومات مدمجة إلى المحطات الأساسية ، مما يؤدي بدوره إلى تحسين فعالية الطاقة وزيادة عمر الشبكات اللاسلكية ذات للطاقة المحدودة. في هذا البحث ، تم اقتراح طريقة تجميع البيانات المستندة إلى النقاط المهمة إدراكيًا (PIP-DA) لشبكات المستشعرات اللاسلكية لتقليل البيانات الزائدة عن الحاجة قبل إرسالها إلى المحطة الاساسية. من خلال استخدام مجموعة بيانات Intel Berkeley Research Lab (IBRL) ، تم قياس كفاءة الطريقة المقترحة. توضح النتائج التجريبية فوائد الطريقة المقترحة حيث تعمل على تقليل الحمل على مستوى عقدة الاستشعار حتى 1.25٪ في البيانات المتبقية وتقليل استهلاك الطاقة حتى 93٪ مقارنة ببروتوكولات PFF و ATP.The transmitting and receiving of data consume the most resources in Wireless Sensor Networks (WSNs). The energy supplied by the battery is the most important resource impacting WSN's lifespan in the sensor node. Therefore, because sensor nodes run from their limited battery, energy-saving is necessary. Data aggregation can be defined as a procedure applied for the elimination of redundant transmissions, and it provides fused information to the base stations, which in turn improves the energy effectiveness and increases the lifespan of energy-constrained WSNs. In this paper, a Perceptually Important Points Based Data Aggregation (PIP-DA) method for Wireless Sensor Networks is suggested to reduce redundant data before sending them to the sink. By utilizing Intel Berkeley Research Lab (IBRL) dataset, the efficiency of the proposed method was measured. The experimental findings illustrate the benefits of the proposed method as it reduces the overhead on the sensor node level up to 1.25% in remaining data and reduces the energy consumption up to 93% compared to prefix frequency filtering (PFF) and ATP protocols

An Energy-Aware Routing Protocol in Wireless Sensor Networks

The most important issue that must be solved in designing a data gathering algorithm for wireless sensor networks (WSNS) is how to save sensor node energy while meeting the needs of applications/users. In this paper, we propose a novel energy-aware routing protocol (EAP) for a long-lived sensor network. EAP achieves a good performance in terms of lifetime by minimizing energy consumption for in-network communications and balancing the energy load among all the nodes. EAP introduces a new clustering parameter for cluster head election, which can better handle the heterogeneous energy capacities. Furthermore, it also introduces a simple but efficient approach, namely, intra-cluster coverage to cope with the area coverage problem. We use a simple temperature sensing application to evaluate the performance of EAP and results show that our protocol significantly outperforms LEACH and HEED in terms of network lifetime and the amount of data gathered

An energy-aware protocol for data gathering applications in wireless sensor networks

2006-2007 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Adaptive Energy Efficient Scheduling (AEES) for Fault Tolerant Coverage in Sensor Networks

For many sensor network applications it is necessary to provide full sensing coverage to a security-sensitive area. To actively monitor the set of target the subset of sensors are redundantly deployed. One of the major challenges in devising such network lies in the constrained energy and to tolerate unexpected failure to prolong the life span of the network. In this we rapidly restore the field monitoring, by periodically refreshing and switching the cover to tackle unanticipated failure in an energy efficient manner, because energy is the most critical resource considering the irreplaceable of batteries of the sensor nodes. In the same time it should amenably support more than one sensor at a time with different degree in distributed approach that periodically selects the covers and switch between them to extend coverage time and tolerate unexpected failures at runtime. In this scheme the sensor is an autonomous system that has the authority to decide how to cover its sensing range. It also incorporates a novel technique for offline cover update (OCU) to facilitate asynchronous transition between covers. This approach is robust to failure pattern is no uniform. DOI: 10.17762/ijritcc2321-8169.15013

Optimization of Energy Efficient Advance Leach Protocol

In WSNs, the only source to save life for the node is the battery consumption. During communication with other area nodes or sensing activities consumes a lot of power energy in processing the data and transmitting the collected/selected data to the sink. In wireless sensor networks, energy conservation is directly to the network lifetime and energy plays an important role in the cluster head selection. A new threshold has been formulated for cluster head selection, which is based on remaining energy of the sensor node and the distance from the base station. Proposed approach selects the cluster head nearer to base station having maximum remaining energy than any other sensor node in multi-hop communication. The multi hop approach minimizing the inter cluster communication without effecting the data reliability

A Review of Wireless Sensor Networks with Cognitive Radio Techniques and Applications

The advent of Wireless Sensor Networks (WSNs) has inspired various sciences and telecommunication with its applications, there is a growing demand for robust methodologies that can ensure extended lifetime. Sensor nodes are small equipment which may hold less electrical energy and preserve it until they reach the destination of the network. The main concern is supposed to carry out sensor routing process along with transferring information. Choosing the best route for transmission in a sensor node is necessary to reach the destination and conserve energy. Clustering in the network is considered to be an effective method for gathering of data and routing through the nodes in wireless sensor networks. The primary requirement is to extend network lifetime by minimizing the consumption of energy. Further integrating cognitive radio technique into sensor networks, that can make smart choices based on knowledge acquisition, reasoning, and information sharing may support the network's complete purposes amid the presence of several limitations and optimal targets. This examination focuses on routing and clustering using metaheuristic techniques and machine learning because these characteristics have a detrimental impact on cognitive radio wireless sensor node lifetime