Improving Performance of WSN Based On Hybrid Range Based Approach

Improving the performance of WSN supported hybrid range based approach. WSN is self-possessed minimization error of nodes prepared with limited resources, limited memory and computational abilities. WSNs reliably work in unidentified hubs and numerous situations, it's difficult to trade sensor hubs after deployment, and therefore a fundamental objective is to optimize the sensor nodes' lifetime. A WSN may be a set of a large number of resource-constrained sensor nodes which have abilities for information detection, processing, and short-range radio communication, Analysis localization error minimization based several applications of wireless sensor networks (WSN) need data regarding the geographical location of each detector node. Self-organization and localization capabilities are one in every of the foremost necessary needs in detector networks. It provides a summary of centralized distance-based algorithms for estimating the positions of nodes during very sensing nodes. Secure localization of unknown nodes during a very wireless detector network (WSN) may be a vital analysis subject wireless sensor networks (WSN), a component of enveloping computing, are presently getting used on a large scale to look at period environmental standing, Be that as it may, these sensors work underneath extraordinary vitality imperatives and are planned by remembering an application. Proposed approaches are sensing node location and challenging task, involve assessing sort of various parameters needed by the target application. In study realize drawback not sense positioning of nodes .but proposed approach formula recognizes the optimal location of nodes supported minimize error and best answer in WSN. Localization algorithms mentioned with their benefits and disadvantages. Lastly, a comparative study of localization algorithms supported the performance in WSN. This was often done primarily to offer a summary of the proposed approach known today for reliable data and minimizing the energy consumption in wireless sensor networks

Traceability of Financial Assets Through the Application of the Internet of Things

Cash continues to be a vital payment method within the United States monetary system, and the use of money continues to grow despite common perception. This research explores the operational behaviors of an armored truck company (ATC) and its interactions with banks, retailers, automatic teller machines (ATMs), and their competitors and establishes a simulation that closely represents a typical branch. Provided data, observed data, and discussions with the management of an ATC validated the simulation model. Next, the research focused on technologies that could be applied to this branch to reduce costs, increase capacity, and improve visibility for all parties in the cash movement process. Through this exploration, passive RFID (radio frequency identification) was chosen as the most optimal solution with the most significant application at the lowest cost of ownership to the ATC branch. After establishing the choice of technology, the simulation model was adapted to include RFID within the operational behaviors of the branch. RFID enables complete system visibility, improves operational behaviors, and significantly decreases operational costs. Adding in an RFID-based sorting robot reduces error and prevents bags from being sorted multiple times by different tellers within the branch. For the branch example used, adding an RFID system saved the ATC branch $2.1 million annually in operational costs and covered the cost of the system deployment. ATCs that deploy RFID within their branches save money, increase capacity, and improve cash visibility

Revisiting the Performance of the Modular Clock Algorithm for Distributed Blind Rendezvous in Cognitive Radio Networks

Abstract. We reexamine the modular clock algorithm for distributed blind rendezvous in cognitive radio networks. It proceeds in rounds. Each round consists of scanning twice a block of generated channels. The modular clock algorithm inspired the creation of the jump-stay ren-dezvous algorithm. It augments the modular clock with a stay-on-one-channel pattern. This enhancement guarantees rendezvous in one round. We make the observation that as the number of channels increases, the significance of the stay-on-one-channel pattern decreases. We revisit the performance analysis of the two-user symmetric case of the modular clock algorithm. We compare its performance with a random and the jump-stay rendezvous algorithms. Let m be the number of channels. Let p be the smallest prime number greater than m. The expected time-to-rendezvous of the random and jump-stay algorithms are m and p, respectively. Theis et al.’s analysis of the modular clock algorithm con-cludes a maximum expected time-to-rendezvous slightly larger than 2p time slots. Our analysis shows that the expected time-to-rendezvous of the modular clock algorithm is no more than 3p/4 time slots.

Multiple-polynomial LFSR based pseudorandom number generator for EPC Gen2 RFID tags

International audienceWe present a lightweight pseudorandom number generator (PRNG) design for EPC Gen2 RFID tags. It is based on a linear feedback shift register (LFSR) configured with multiple feedback polynomials that are selected by a physical source of randomness. The proposal successfully handles the inherent linearity of LFSR based PRNGs and satisfies the statistical requirements imposed by the EPC Gen2 standard. Statistical analysis of the sequences generated by our generator confirms the validity of the proposed technique.We show that our proposal has, moreover, a simpler hardware implementation and energy consumption than previous designs reported in the literature

Formal Verification of a Key Establishment Protocol for EPC Gen2 RFID Systems: Work in Progress

International audienceThe EPC Class-1 Generation-2 (Gen2 for short) is a standard Radio Frequency Identification (RFID) technology that has gained a prominent place on the retail industry. The Gen2 standard lacks, however, of verifiable security functionalities. Eavesdropping attacks can, for instance, affect the security of monitoring applications based on the Gen2 technology. We are working on a key establishment protocol that aims at addressing this problem. The protocol is applied at both the initial identification phase and those remainder operations that may require security, such as password protected operations. We specify the protocol using the High Level Protocol Specification Language (HLPSL). Then, we verify the secrecy property of the protocol using the AVISPA model checker tool. The results that we report show that the current version of the protocol guarantees sensitive data secrecy under the presence of a passive adversary

Secure Protocols for Key Pre-distribution, Network Discovery, and Aggregation in Wireless Sensor Networks

The term sensor network is used to refer to a broad class of networks where several small devices, called sensors, are deployed in order to gather data and report back to one or more base stations. Traditionally, sensors are assumed to be small, low-cost, battery-powered, wireless, computationally constrained, and memory constrained devices equipped with some sort of specialized sensing equipment. In many settings, these sensors must be resilient to individual node failure and malicious attacks by an adversary, despite their constrained nature. This thesis is concerned with security during all phases of a sensor network's lifetime: pre-deployment, deployment, operation, and maintenance. This is accomplished by pre-loading nodes with symmetric keys according to a new family of combinatorial key pre-distribution schemes to facilitate secure communication between nodes using minimal storage overhead, and without requiring expensive public-key operations. This key pre-distribution technique is then utilized to construct a secure network discovery protocol, which allows a node to correctly learn the local network topology, even in the presence of active malicious nodes. Finally, a family of secure aggregation protocols are presented that allow for data to be efficiently collected from the entire network at a much lower cost than collecting readings individually, even if an active adversary is present. The key pre-distribution schemes are built from a family of combinatorial designs that allow for a concise mathematical analysis of their performance, but unlike previous approaches, do not suffer from strict constraints on the network size or number of keys per node. The network discovery protocol is focused on providing nodes with an accurate view of the complete topology so that multiple node-disjoint paths can be established to a destination, even if an adversary is present at the time of deployment. This property allows for the use of many existing multi-path protocols that rely on the existence of such node-disjoint paths. The aggregation protocols are the first designed for simple linear networks, but generalize naturally to other classes of networks. Proofs of security are provided for all protocols

Trust assessment in 32 KiB of RAM : multi-application trust-based task offloading for resource-constrained IoT nodes

There is an increasing demand for Internet of Things (IoT) systems comprised of resource-constrained sensor and actuator nodes executing increasingly complex applications, possibly simultaneously. IoT devices will not be able to execute computationally expensive tasks and will require more powerful computing nodes, called edge nodes, for such execution, in a process called computation offloading. When multiple powerful nodes are available, a selection problem arises: which edge node should a task be submitted to? This problem is even more acute when the system is subjected to attacks, such as DoS, or network perturbations such as system overload. In this paper, we present a trust model-based system architecture for computation offloading, based on behavioural evidence. The system architecture provides confidentiality, authentication and non-repudiation of messages in required scenarios and will operate within the resource constraints of embedded IoT nodes. We demonstrate the viability of the architecture with an example deployment of Beta Reputation System trust model on real hardware

Threat Modelling Guided Trust-based Task Offloading for Resource-constrained Internet of Things

There is an increasing demand for Internet of Things (IoT) networks consisting of resource-constrained devices executing increasingly complex applications. Due to these resource-constraints, IoT devices will not be able to execute expensive tasks. One solution is to offload expensive tasks to resource-rich edge nodes. Which requires a framework that facilitates the selection of suitable edge nodes to perform task offloading. Therefore, in this paper, we present a novel trust model-driven system architecture, based on behavioural evidence, that is suitable for resource-constrained IoT devices that supports computation offloading. We demonstrate the viability of the proposed architecture with an example deployment of the Beta Reputation System trust model on real hardware to capture node behaviours. The open environment of edge-based IoT networks means that threats against edge nodes can lead to deviation from expected behaviour. Hence, we perform a threat modelling to identify such threats. The proposed system architecture includes threat handling mechanisms that provide security properties such as confidentiality, authentication and non-repudiation of messages in required scenarios and operate within the resource constraints. We evaluate the efficacy of the threat handling mechanisms and identify future work for the standards used