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In radio frequency identification (RFID) systems, the reader identifies tags through communication over a shared wireless channel. When multiple tags transmit their IDs simultaneously, their signals collide, increasing the identification delay. Therefore, many previous anti-collision algorithms, including an adaptive query splitting algorithm (AQS) and an adaptive binary splitting algorithm (ABS), focused on solving this problem. This paper proposes two blocking algorithms, a single resolution blocking ABS algorithm (SRB) and a pair resolution blocking ABS algorithm (PRB), based on ABS. SRB not only inherits the essence of ABS which uses the information of recognized tags obtained from the last process of tag identification, but also adopts a blocking technique which prevents recognized tags from being collided by unrecognized tags. PRB further adopts a pair resolution technique which couples recognized tags and thus only needs half time for next identifying these recognized tags. We formally analyze the performance of SRB and PRB. Finally, the analytic and simulation results show that SRB slightly outperforms ABS and PRB significantly surpasses ABS. [ABSTRACT FROM AUTHOR]

In wireless mesh networks, the end-to-end throughput of traffic flows depends on the path length, i.e., the higher the number of hops, the lower becomes the throughput. In this paper, a fair end-to-end bandwidth allocation (FEBA) algorithm is introduced to solve this problem. FEBA is implemented at the medium access control (MAC) layer of single-radio, multiple channels IEEE 802.16 mesh nodes, operated in a distributed coordinated scheduling mode. FEBA negotiates bandwidth among neighbors to assign a fair share proportional to a specified weight to each end-to-end traffic flow. This way traffic flows are served in a differentiated manner, with higher priority traffic flows being allocated more bandwidth on the average than the lower priority traffic flows. In fact, a node requests/grants bandwidth from/to its neighbors in a round-robin fashion where the amount of service depends on both the load on its different links and the priority of currently active traffic flows. If multiple channels are available, they are all shared evenly in order to increase the network capacity due to frequency reuse. The performance of FEBA is evaluated by extensive simulations. It is shown that wireless resources are shared fairly among best-effort traffic flows, while multimedia streams are provided with a differentiated service that enables quality of service. [ABSTRACT FROM AUTHOR]

We study network optimization that considers power minimization as an objective. Studies have shown that mechanisms such as speed scaling can significantly reduce the power consumption of telecommunication networks by matching the consumption of each network element to the amount of processing required for its carried traffic. Most existing research on speed scaling focuses on a single network element in isolation. We aim for a network-wide optimization. Specifically, we study a routing problem with the objective of provisioning guaranteed speed/bandwidth for a given demand matrix while minimizing power consumption. Optimizing the routes critically relies on the characteristic of the speed–power curve f(s), which is how power is consumed as a function of the processing speed s. If f is superadditive, we show that there is no bounded approximation in general for integral routing, i.e., each traffic demand follows a single path. This contrasts with the well-known logarithmic approximation for subadditive functions. However, for common speed–power curves such as polynomials f(s) = \mu s^\alpha, we are able to show a constant approximation via a simple scheme of randomized rounding. We also generalize this rounding approach to handle the case in which a nonzero startup cost \sigma appears in the speed–power curve, i.e., f(s) = \cases0, & if $s=0$\cr \sigma + \mu s^\alpha,& if $s>0$. We present an O((\sigma /\mu)^1/\alpha)-approximation, and we discuss why coming up with an approximation ratio independent of the startup cost may be hard. Finally, we provide simulation results to validate our algorithmic approaches. [ABSTRACT FROM PUBLISHER]

Many distributed applications require a group of destinations to be coordinated with a single source. Multicasting is a communication paradigm to implement these distributed applications. However in multicasting, if at least one of the members in the group cannot satisfy the service requirement of the application, the multicast request is said to be blocked. On the contrary in manycasting, destinations can join or leave the group, depending on whether it satisfies the service requirement or not. This dynamic membership based destination group decreases request blocking. We study the behavior of manycasting over optical burst-switched networks (OBS) based on multiple quality of service (QoS) constraints. These multiple constraints can be in the form of physical-layer impairments, transmission delay, and reliability of the link. Each application requires its own QoS threshold attributes. Destinations qualify only if they satisfy the required QoS constraints set up by the application. We have developed a mathematical model based on lattice algebra for this multiconstraint problem. Due to multiple constraints, burst blocking could be high. We propose two algorithms to minimize request blocking for the multiconstrained manycast (MCM) problem. Using extensive simulation results, we have calculated the average request blocking for the proposed algorithms. Our simulation results show that MCM-shortest path tree (MCM-SPT) algorithm performs better than MCM-dynamic membership (MCM-DM) for delay constrained services and real-time service, where as data services can be better provisioned using MCM-DM algorithm. [ABSTRACT FROM AUTHOR]

We design a resource allocation algorithm for down-link of orthogonal frequency division multiple access (OFDMA) systems supporting real-time (RT) and best-effort (BE) services simultaneously over a time-varying wireless channel. The proposed algorithm aims at maximizing system throughput while satisfying quality of service (QoS) requirements of the RT and BE services. We take two kinds of QoS requirements into account. One is the required average transmission rate for both RT and BE services. The other is the tolerable average absolute deviation of transmission rate (AADTR) just for the RT services, which is used to control the fluctuation in transmission rates and to limit the RT packet delay to a moderate level. We formulate the optimization problem representing the resource allocation under consideration and solve it by using the dual optimization technique and the projection stochastic subgradient method. Simulation results show that the proposed algorithm well meets the QoS requirements with the high throughput and outperforms the modified largest weighted delay first (M-LWDF) algorithm that supports similar QoS requirements. [ABSTRACT FROM AUTHOR]