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.
In @cite_15 , the Tree Slotted Aloha (TSA) protocol is proposed. It aims to reduce tag transmission collisions by querying only those tags colliding in the same slot of a previous frame of transmissions. At the end of each frame, for each slot in which a collision occurred, the reader starts a new small frame, reserved to those tags which collided in the same time slot. In this way, a transmission frame can be viewed as a node in a tree, where the root is the initial frame; leaves represent frames where no collision occurred.
@cite_15
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In this paper, we approach the problem of identifying a set of objects in an RFID network. We propose a modified version of slotted aloha protocol to reduce the number of transmission collisions. All tags select a slot to transmit their ID by generating a random number. If there is a collision in a slot, the reader broadcasts the next identification request only to tags which collided in that slot. Simulation results show that our approach performs better than framed slotted aloha and query tree based protocols, in terms of number of slots needed to identify all tags, which is a commonly used metric, strictly related to delay. This paper analyses the practical faults existing in enhanced dynamic frame slotted ALOHA (EDFSA) algorithms, and discusses the strategy to improve the efficiency of anti-collision algorithm in RFID system. EDFSA algorithm divides the tags into a number of groups and allows only one group of tags to respond when the number of tags is much larger than optimal efficiency tags. However the efficiency of the system can still be improved. We propose a new anti-collision algorithm called by the name of variant enhanced dynamic frame slotted ALOHA algorithm (VEDFSA) to improve the efficiency of the system that can solve the problem above by dynamic divide tags into groups during the anti-collision solving procedure. In RFID system, one of the problems that we must solve is the collision between tags which lowers the efficiency of the RFID system. One of the popular anti-collision algorithms is ALOHA-type algorithms, which are simple and shows good performance when the number of tags to read is small. However, they generally require exponentially increasing number of slots to identify the tags as the number of tag increases. In the paper, we propose a new anti-collision algorithm called enhanced dynamic framed slotted ALOHA (EDFSA) which estimates the number of unread tags first and adjusts the number of responding tags or the frame size to give the optimal system efficiency. As a result, in the proposed method, the number of slots to read the tags increases linearly as the the number of tags does. Simulation results show that the proposed algorithm improves the slot efficiency by 85 spl sim 100 compared to the conventional algorithms when the number of tags is 1000. This paper presents a novel Medium Access Control (MAC) protocol named ALOHA and Q-Learning based MAC with Informed Receiving (ALOHA-QIR) for Wireless Sensor Networks (WSNs). This scheme is implemented by combining frame based Slotted ALOHA and Q-Learning. ALOHA based schemes have the benefits of simplicity, low computation and overheads, but suffer collisions from the blind transmission strategy. By considering the previous transmission experience, Q-Learning offers nodes certain intelligence to access slots with a lower probability of collision. During data transmissions, receivers are informed by transmitters about their future slot selections so that the receivers can turn off their radio in other slots to save energy. Compared with basic Slotted ALOHA, ALOHA-QIR obtains significant improvements in throughput, delay and energy efficiency.