Perfect tag identification protocol in RFID networks

Radio Frequency IDentification (RFID) systems are becoming more and more popular in the field of ubiquitous computing, in particular for objects identification. An RFID system is composed by one or more readers and a number of tags. One of the main issues in an RFID network is the fast and reliable identification of all tags in the reader range. The reader issues some queries, and tags properly answer. Then, the reader must identify the tags from such answers. This is crucial for most applications. Since the transmission medium is shared, the typical problem to be faced is a MAC-like one, i.e. to avoid or limit the number of tags transmission collisions. We propose a protocol which, under some assumptions about transmission techniques, always achieves a 100% perfomance. It is based on a proper recursive splitting of the concurrent tags sets, until all tags have been identified. The other approaches present in literature have performances of about 42% in the average at most. The counterpart is a more sophisticated hardware to be deployed in the manufacture of low cost tags.Comment: 12 pages, 1 figur

A survey on subjecting electronic product code and non-ID objects to IP identification

Over the last decade, both research on the Internet of Things (IoT) and real-world IoT applications have grown exponentially. The IoT provides us with smarter cities, intelligent homes, and generally more comfortable lives. However, the introduction of these devices has led to several new challenges that must be addressed. One of the critical challenges facing interacting with IoT devices is to address billions of devices (things) around the world, including computers, tablets, smartphones, wearable devices, sensors, and embedded computers, and so on. This article provides a survey on subjecting Electronic Product Code and non-ID objects to IP identification for IoT devices, including their advantages and disadvantages thereof. Different metrics are here proposed and used for evaluating these methods. In particular, the main methods are evaluated in terms of their: (i) computational overhead, (ii) scalability, (iii) adaptability, (iv) implementation cost, and (v) whether applicable to already ID-based objects and presented in tabular format. Finally, the article proves that this field of research will still be ongoing, but any new technique must favorably offer the mentioned five evaluative parameters.Comment: 112 references, 8 figures, 6 tables, Journal of Engineering Reports, Wiley, 2020 (Open Access

Tag anti-collision algorithms in RFID systems - a new trend

RFID is a wireless communication technology that provides automatic identification or tracking and data collection from any tagged object. Due to the shared communication channel between the reader and the tags during the identification process in RFID systems, many tags may communicate with the reader at the same time, which causes collisions. The problem of tag collision has to be addressed to have fast multiple tag identification process. There are two main approaches to the tag collision problem: ALOHA based algorithms and tree based algorithms. Although these methods reduce the collision and solve the problem to some extent, they are not fast and efficient enough in real applications. A new trend emerged recently which takes the advantages of both ALOHA and tree based approaches. This paper describes the process and performance of the tag anti-collision algorithms of the tree-ALOHA trend

Energy aware improved least and most significant bit arbitration algorithm for WORM tags

AbstractPassive Radio Frequency Identification systems have gained enormous attention and popularity especially after its adoption in time and data critical systems. Theoretically, these systems have the potential to read over 100 tags per second in applications which are well insulated from RF noise. Nevertheless, this may not be the case in practical systems, as tag collision is one of the major deterrents affecting the recognition rate. This paper exhaustively analyses the existing probabilistic, deterministic and hybrid algorithms on collision resolutions. In probabilistic algorithms, tags send their entire ID to the RFID reader in respective slots while tags in deterministic algorithms respond bit by bit based on the RFID reader’s query. To minimize identification delay, tag communication overhead and high energy consumption, a new energy efficient collision resolution strategy named Improved Least and Most Significant Bit Algorithm (LaMSBA) is introduced to effectively singulate a tag and increase the identification efficiency in changing tag population even when the bits in tag ID’s are randomly or uniformly distributed. Extensive simulation studies show that LaMSBA can be chosen as better alternatives for dense time and data critical RFID enabled systems. In addition, M/G/1 Queuing model is suitably identified and the the analytical results concluded that LaMSBA is able to maintain the steady state condition even when Class 1 tags arrive at the rate of 15 tags/second in the reader’s interrogation zone

Parallel Construction of Wavelet Trees on Multicore Architectures

The wavelet tree has become a very useful data structure to efficiently represent and query large volumes of data in many different domains, from bioinformatics to geographic information systems. One problem with wavelet trees is their construction time. In this paper, we introduce two algorithms that reduce the time complexity of a wavelet tree's construction by taking advantage of nowadays ubiquitous multicore machines. Our first algorithm constructs all the levels of the wavelet in parallel in $O(n)$ time and $O(n\lg\sigma + \sigma\lg n)$ bits of working space, where $n$ is the size of the input sequence and $\sigma$ is the size of the alphabet. Our second algorithm constructs the wavelet tree in a domain-decomposition fashion, using our first algorithm in each segment, reaching $O(\lg n)$ time and $O(n\lg\sigma + p\sigma\lg n/\lg\sigma)$ bits of extra space, where $p$ is the number of available cores. Both algorithms are practical and report good speedup for large real datasets.Comment: This research has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sk{\l}odowska-Curie Actions H2020-MSCA-RISE-2015 BIRDS GA No. 69094