RFID and Sensor Networks: Architectures, Protocols, Security

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Cluster Cluster head Cluster head Data Aggregation in Wireless Sensor Networks � 307 Cluster Figure 11.4 Cluster-based data aggregation. Cluster head Cluster Base station To be a cluster head, a sensor node n picks a random random number between [0,1] and becomes a cluster head if this number is lower than T (n). Cluster head advertisements are broadcasted to sensor nodes and sensor nodes join the clusters based on the signal strength of the advertisement messages. Based on the number of cluster members, each cluster head schedules its cluster based on TDMA to optimally manage the local transmissions. In the second phase, sensor nodes send their data to cluster heads according to the established schedule. Optionally, sensor nodes may turn off their radios until their scheduled TDMA transmission slot. LEACH requires cluster heads to send their aggregated data to the base station over a single link. However, this is a disadvantage of LEACH because single link transmission may be quite expensive when the base station is far away from the cluster head. LEACH is completely distributed as it does not require any global knowledge regarding network structure. It is also an adaptive protocol in terms of cluster head selection. On the other hand, there may be high control message overhead if the network topology is dynamic due to mobile nodes. Another cluster-based data aggregation protocol, called HEED, is proposed in Ref. [20]. For cluster head selection, HEED benefits from the availability of multiple power levels at sensor nodes. In fact, a combined metric is composed of the node’s residual energy and the node’s proximity to its neighbors. HEED defines the average of the minimum power level required by all sensor nodes within the cluster to reach the cluster head. This is called Average Minimum Reachability Power (AMRP). AMPR is used to estimate the communication cost in each cluster. To select cluster heads, each sensor node computes its probability of becoming the cluster head as follows: P(CH) = C × Eresidual Emax
308 � RFID and Sensor Networks where the initial percentage of cluster heads is denoted by C and Eresidual and Emax represent the current residual and initial energy of the sensor node, respectively. Each sensor node broadcasts a cluster head message; sensor nodes select their cluster head as the node with the lowest AMRP in the set of received cluster head messages. This process recursively continues until every node is assigned to a cluster head. Similar to LEACH, in HEED, cluster heads directly communicate with the base station. Simulation results show that HEED extends the network lifetime and results in geographically balanced set of cluster heads. In Ref. [21], a clustering scheme that performs periodic perhop data aggregation is proposed. The proposed scheme, called Cougar, is suitable for applications where sensor nodes continuously generate correlated data. Once cluster heads aggregate their cluster data, they send the local aggregated data to a gateway node. Similar to LEACH, Cougar is negatively affected from dynamic network topologies, however Cougar has a unique cluster head election procedure. Cougar selects the cluster heads based on more than one metric and allows sensor nodes to be more than one hop away from their cluster heads. This calls for routing algorithms to exchange packets within clusters. Cougar employs the Ad Hoc On Demand Distance Vector (AODV) protocol for inter cluster relaying. In Cougar, a synchronization mechanism is used to correctly aggregate the data. The cluster head is synchronized with all sensor nodes in the cluster and it does not report its aggregated data to the gateway node until all sensor nodes send their data. Clustered Diffusion with Dynamic Data Aggregation (CLUDDA) [22] is a hybrid approach that combines clustering with diffusion mechanisms. CLUDDA includes query definitions inside interest messages which are initiated by the base station. Each interest message contains the definition of the query that describes the operations that need to be performed on the data components to generate a proper response. Interest transformation reduces the processing overhead by utilizing the existing knowledge of queries. CLUDDA combines Directed Diffusion [11] and clustering during the initial phase of interest propagation. Using clustering mechanism, it is ensured that only cluster heads that perform inter cluster communication are involved in the transmission of interest messages. As the regular sensor nodes do not transmit any data unless they are capable of servicing a request, CLUDDA conserves energy. In CLUDDA, any cluster head that has the knowledge of query definition can perform data aggregation, hence the aggregation points are dynamic. Also, each cluster head maintains a query cache to present the different data components that were aggregated to obtain the final data. Cluster heads also keep a list of the addresses of neighboring nodes from which the data messages originated. These addresses are used to propagate interest messages directly to specific nodes instead of broadcasting. Some other cluster-based protocols for data aggregation have been proposed in the literature. Some of them are improvements of existing protocols. In Ref. [24], a crosslayer approach is adopted by integrating MAC design into data aggregation concept. A location-based clustering scheme where the sensors self-organize to form static clusters is developed in Ref. [25]. Sensor nodes send their data to cluster head along shortest paths, and in-network aggregation is performed at the intermediate nodes. Cluster heads perform aggregation and send aggregated data to the base station over multihop paths.
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Contents Preface...................
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Contents � vii 21 Integrated RFID
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x � Preface WSNs. This book conta
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xii � Editors of Cluster Computin
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Contributors Nadjib Achir Institut
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Lin Li Department of Computer Scien
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Bashir Yahya PRiSM Laboratory Unive
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Chapter 1 Medium Access Control in
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Medium Access Control in RFID � 5
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Broadcast/synchronization Reader f
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1010 101C 1C1C 1011 Medium Access C
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Chapter 4 EPC Gen-2 Standard for RF
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4.1 Introduction EPC Gen-2 Standard
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EPC Gen-2 Standard for RFID � 101
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Data 0 EPC Gen-2 Standard for RFID
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Chapter 6 RFID Security Denis Trče
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Index A ABS protocol, 51-52 Access
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C legal implications, 178, 180 mand
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eactive data-centric protocol, 304
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tag singulation EPC Gen-2 tag data
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History-based control method, mobil
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analog front end and antenna design
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N NAND gates, 154-156 Network maint
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phase transitional motivators (PTM)
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Sensor-monitoring module, 575 Senso
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Taxonomy, clustering protocols, 331
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