Radio frequency identification suffers from tag collision issue. ALOHA-based algorithms are useful and practical groups of tag anti-collision algorithm among others. Some standards such as EPCglobal Class-1 Generation-2 use some kind of dynamic framed slotted ALOHA (DFSA) to cope with tag collision. DFSA efficiency depends on estimating the number of unidentified tags in each identification cycle accurately. So tag estimation is one of the challenging issues in DFSA. In this paper, we use Manchester coding to compute the lower bound of collided tags in a frame and then add α as an additional value to computed value according to the difference between optimal number of collision slots and calculated number of collision slots. Then, we evaluate and compare our method with other proposed methods. KEYWORDS DFSA, RFID, tag anti-collision, tag estimation | INTRODUCTIONThe automatic identification and data capture (AIDC) technology was introduced to simplify the way of identification. Among other members of this technology including optical character recognition (OCR), barcode and infrared identification technologies, and the radio frequency identification (RFID) could be called the rising star in this family because of its characteristics: nonline-of-sight and contactless reading data. 1 RFID comprises three elements: tags that store data, reader that reads/writes data from/to tags within its interrogation zone, and a server to analyze received data from reader. The basic of identification process in RFID is easy to understand; first, reader transmits adequate energy to power up the tags, then communicate with tags to demand, and receive their identifiers (ID). One of the benefits of RFID rather than some other auto ID technologies like barcode is reading more than one tag simultaneously via a reader. But this benefit causes side effects like collision. It is reported that in typical RFID deployments, the tag read rate is usually about 60% to 70%. 2 There are two main types of collision: tag collision and reader collision. Tag collision happens when more than one tag within interrogation zone of a reader transmit their data to that reader simultaneously. Result of this transmission is receiving of corruption signals by reader. Reader collision happens when one tag is within interrogation zone of two or more readers and they want to read that tag simultaneously. Both reader and tag collision are depicted in Figure 1. To address this issue tag and reader anti-collision is proposed, but our focus in this paper is on tag anti-collision algorithms. There are four types of tag anti-collision algorithms: ALOHA-based, tree-based, counter-based, and some algorithms that are made by combination of the first three types, called hybrid algorithms. 3 ALOHA-based algorithms like framed slotted ALOHA (FSA) use frame that comprises some slots, and then, each tag can transmit its data in a slot. These algorithms are probabilistic. 4-7 Tree-based algorithms like query tree divide all collided tags to two groups according to bits of thei...
Data collection is an essential task in Wireless Sensor Networks (WSNs). In data collection process, the sensor nodes transmit their readings to a common base station called Sink. To avoid a collision, it is necessary to use the appropriate scheduling algorithms for data transmission. On the other hand, multi-channel design is considered as a promising technique to reduce network interference and latency of data collection. This technique allows parallel transmissions on different frequency channels, thus time latency will be reduced. In this paper, we present a new scheduling method for multi-channel WSNs called Balanced Multi Channel Data Collection (Balanced MC-DC) Algorithm. The proposed protocol is based on using both Non-Overlapping Channels (NOC) and Partially Overlapping Channels (POC). It uses a new approach that optimizes the processes of tree construction, channel allocation, transmission scheduling and balancing simultaneously. Extensive simulations confirm the superiority of the proposed algorithm over the existing algorithms in wireless sensor networks.
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