IGAA: An Efficient Optimization Technique for RFID Network Topology Design in Internet of Things

[[abstract]]Most RFID applications in the Internet of Things (IoTs) use multiple readers to read the IDs of multiple tags and form the RFID network. In such a network, unguarded reader deployment may generate over-crowded readers, cause interferences and, as a result, increases the deployment cost while degrading tag detection. Seeing that desirable reader deployment is crucial for RFID system performance, this paper introduces an optimization-based IGAA approach which outperforms existing RFID topology designs by turning up more favorable reader deployment and system performance. The new approach employs an advanced multi-objective fitness function and improved genetic annealing algorithms (GAA) to pursue a better RFID topology design. By involving an improved gene-stirring operation to help preserve good genes and locate optimal solutions for reader deployment, it is simple in operation but effective in practice. Experimental evaluation shows that when compared with related approaches, IGAA can yield better solution quality with less search time.[[notice]]補正完畢[[incitationindex]]EI[[booktype]]紙本[[booktype]]電子

Optimization of RFID Network Planning Using MDB-FA Method

Topology network design in RFID Network Planning (RNP) is the most important factor in hard optimization problems of network planning. Reader distribution is highly impacted by topological tags distribution. The integration of RFID multi-objective network planning with the network topology design results in better capability of reader distribution. Thus, this paper evaluates the impact of topological network design to support the RFID reader’s distribution system. Monte Carlo simulation (MCS) is used to generate tag distribution based on network topology design modules as a method to evaluate the deterministic indicators in NP-hard problems. The generated data are utilized as an input representation to apply into firefly algorithm based on Density- Based Algorithm (DBSCAN) to find the optimal network solution. Experimental results show the effectiveness of the method in L-Shape RNP, and show that the proposed algorithm is capable of achieving high coverage and use of fewer readers in actual conditions of warehouse design

Cost and Lightweight Modeling Analysis of RFID Authentication Protocols in Resource Constraint Internet of Things

Internet of Things (IoT) is a pervasive environment to interconnect the things like: smart objects, devices etc. in a structure like internet. Things can be interconnected in IoT if these are uniquely addressable and identifiable. Radio Frequency Identification (RFID) is one the important radio frequency based addressing scheme in IoT. Major security challenge in resource constraint RFID networks is how to achieve traditional CIA security i.e. Confidentiality, Integrity and Authentication. Computational and communication costs for Lightweight Mutual Authentication Protocol (LMAP), RFID mutual Authentication Protocol with Permutation (RAPP) and kazahaya authentication protocols are analyzed. These authentication protocols are modeled to analyze the delays using lightweight modeling language. Delay analysis is performed using alloy model over LMAP, RAPP and kazahaya authentication protocols where one datacenter (DC) is connected to different number of readers (1,5 or 10) with connectivity to 1, 5 or 25 tags associated with reader and its results show that for LMAP delay varies from 30-156 msec, for RAPP from 31-188 while for kazahaya from 61-374 msec. Further, performance of RFID authentication protocols is analyzed for group construction through more than one DC (1,5 or 10) with different number of readers (10, 50 or 100) and tags associated with these readers (50, 500, 1000) and results show that DC based binary tree topology with LMAP authentication protocol is having a minimum delay for 50 or 100 readers. Other authentication protocols fail to give authentication results because of large delays in the network. Thus, RAPP and Kazahaya are not suitable for scenarios where there is large amount of increase in number of tags or readers

RFID network topology design based on Genetic Algorithms

Abstract — Radio Frequency Identification (RFID) is a well known technology that has entered successfully in the realm of innumerable applications and is considered as one of the principal building blocks for the realization of the Internet of Things concept. However, the majority of RFID applications require the utilization of multiple RFID readers and therefore effective and efficient planning of their networks is a major concern. Network planning is a complex process that involves different steps, one of which is its topology design. In this paper, we focus on the topology design process of a RFID network following an optimization-based approach. More precisely, we propose a multi-objective cost function that is used to evaluate candidate solutions for the position and power levels of the set of RFID readers to be deployed. In order to obtain optimal solutions we applied Genetic Algorithms, a well known heuristic technique. Finally, a developed software tool to assist in the topology design is also presented and processing delay measurements are performed