The demand and supply problems are encountered widely in almost all fields. While the users hope to get their demand satisfied always, the suppliers do not want to produce superfluous supplies. One way to tackle this problem is to have a good prediction on the future demand. Many forecasting algorithms have been proposed by using time series and extrapolation techniques. However, most of the algorithms are based on the complex theories and consume potentially large amount computing resources. In this paper, we propose a new algorithm to predict the demand by applying classical learning automata techniques. The algorithm uses more concise strategies and consumes considerably less computing resources.

Software-defined networking (SDN) has received tremendous attention from both industry and academia. The centralized control plane in SDN has a global view of the network and can be used to provide more effective solutions for complex problems, such as traffic engineering. This study is motivated by recent advancement in SDN and increasing popularity of multicasting applications. We propose a technique to increase the resiliency of multicasting in SDN based on the subtree protection mechanism. Multicasting is a group communication technology, which uses the network infrastructure efficiently by sending the data only once from one or multiple sources to a group of receivers that share a common path. Multicasting applications, e.g., live video streaming and video conferencing, become popular, but they are delay-sensitive applications. Failures in an ongoing multicast session can cause packet losses and delay, which can significantly affect quality of service (QoS). In this study, we adapt a subtree-based technique to protect a multicast tree constructed for OpenFlow switches in SDN. The proposed algorithm can detect link or node failures from a multicast tree and then determines which part of the multicast tree requires changes in the flow table to recover from the failure. With a centralized controller in SDN, the backup paths can be created much more effectively in comparison to the signaling approach used in traditional multiprotocol label switching (MPLS) networks for backup paths, which makes the subtree-based protection mechanism feasible. We also implement a prototype of the algorithm in the POX controller and measure its performance by emulating failures in different tree topologies in Mininet.

In the pursuit of ever increasing demand of higher data rates, modern wireless communication systems are resorting to tighter frequency reuse patterns thereby leading to interference-limited systems. Recently proposed interference-aware receiver [1] is a low complexity and efficient receiver design for interference mitigation in cellular systems. However this advanced receiver necessitates the channel knowledge of both the desired and interfering signals which may not be available in a practical system. In this paper, we investigate the performance of interference-aware receiver under imperfect channel state information (CSI). We consider uncorrelated Rayleigh flat fading channels and model the estimation error as independent complex Gaussian random variables. We derive upper bound on the pair wise error probability (PEP) and show that the interference-aware receiver is characterized by full diversity in the presence of channel estimation errors. We compare the performance of interference-aware receiver with that of MMSE receiver and show that the degradation in the performance of MMSE receiver is much more pronounced than that of interference-aware receiver under imperfect CSI.

Network Coding is a relatively new forwarding paradigm where intermediate nodes perform a store, code, and forward operation on incoming packets. Traditional forwarding approaches, which employed a store and forward operation, suffered from the limitations of the max-flow min-cut theorem wherein sources transmitting information over bottleneck links had to compete for access to these links. With Network Coding, multiple sources are now able to transmit packets over bottleneck links simultaneously, increasing network capacity. While the majority of the contemporary literature has focused on the performance of Network Coding from a capacity perspective, the aim of this research has taken a new direction focusing on two Quality of Service metrics, Packet Delivery Ratio (PDR) and latency, in conjunction with Network Coding protocols in Mobile Ad-Hoc Networks (MANETs). Initial simulations will be performed on static environments to determine a Quality of Service baseline comparison between Network Coding protocols and traditional ad-hoc routing protocols. Additional simulations will then be performed for mobile scenarios to determine how the Network Coding protocols will compare to that of the standard ad-hoc routing protocols in the presence of mobility.

This paper addresses the Quality of Service (QoS) degradation problem of wireless relay node failures in multihop Worldwide interoperable Microwave Access (WiMAX) and Long Term Evolution (LTE) networks. In general, node protection in a communication network increases the reliability of the traffic flow from source to destination. For wireless networks, implementing the traditional 1+1 protection scheme increases the capital cost, as resources cannot be fully utilized. On the other hand, the design and implementation of the 1:N protection scheme in wireless networks for greater value of N (> 2) is very difficult, due to wireless network coverage and the physical layer design. To overcome the above drawbacks, a technique based on network coding is proposed for node protection in multihop wireless networks. In multihop wireless networks, few research efforts are concentrated on node protection schemes using network coding. Moreover, to best of our knowledge, no reports have been published on measuring the QoS performance for node protection in 4G wireless networks using network coding. In this paper, we first describe the node protection scheme using XOR network coding for multihop 4G wireless networks. Then, we measure the QoS performance, such as packet delivery ratio (PDR), latency and jitter, for different scenarios. The scenarios include a failure of a single relay node and failures of two relay nodes with and without our protection scheme and user's mobility. The simulation results show that the QoS performance with protection against a single relay node failure and failures of two relay nodes are very close to that of no failure scenario, while the network reliability increases due to the protection mechanism. Also, we report a decoding problem in multihop wireless networks using XOR network coding.

WiMAX technology provides a Quality of Service (QoS) system that allows system operators to configure a network to provide maximum performance compared to conventional Best Effort (BE) systems. In this paper, we address the increase in number of data rich mobile devices and the performance issues associated with Video On Demand (VOD) multimedia traffic over a WiMAX network. We present the results of application testing using WiMAX protocol where the main focus is to show how utilizing a QoS system can benefit streaming real time multimedia. The results show how WiMAX technology is beneficial to multimedia applications.

Streaming over peer-to-peer (P2P) network is popular, however causes needless traffic traversal through multiple links due to the mismatch between the physical and the overlay network. Cellular channels are limited in number and expensive. Because of the magnitude of contents per unit time and the nature of playing same contents throughout the entire system, collaborative streaming approach is the key to an efficient P2P streaming system. In this paper, we propose a collaborative streaming system where some cellular peers download contents from the Internet peers, and then share the contents with the remaining cellular peers by employing device-to-device (D2D) multicast application in order to avoid bottleneck at the eNodeB (eNB), and to reduce streaming cost. We present the broadcasters/agents and their optimal assisted peers selection problem as stable admission assignment and formulate the problem as integer linear programming (ILP) problem. We also present a distributed algorithm to select agents among the cellular peers with suitable number of assisted peers for each agent to tackle the retransmission problem. The cellular peers change role as a broadcaster or a multicast receiver to ensure fairness. We also perform extensive simulation to show the efficacy of our design and to verify our claims.

A Smart grid is characterized by two-way flows of power in electrical networks and information in communication networks [1]. The characteristics of communications in a smart grid vary for different applications that exist between control centers and power generating stations, distribution stations and consumer areas. For effective communications, proper communication network design and the selection of technology is essential. In this paper, we analyze the communication requirements of smart grids in electrical power distribution areas and in consumer places. As the communication in a Distribution Area Network (DAN) integrate the AMIs payload from the consumer area, it is necessary to analyze the data flow from the consumer area to control centers through a DAN. Few communication technologies are available to implement the DAN. Among that, WiMAX and LTE are more suitable than other technologies, as they satisfy the communication requirements and the cost. Little research has been conducted on analyzing and simulating the DAN by considering various applications that exist in a DAN. In this paper, we measure the smart metering capacity and the Quality of Service (QoS) performance (packet loss and latency) of DAN using WiMAX technology. From the obtained results, we also suggest that the 4G technologies are (WiMAX and LTE) more suitable candidate than existing cellular and wire line technologies for implementing the DAN in smart grids.

Selection of Call Admission Control (CAC) and packet scheduling are crucial for multihop WiMAX networks to satisfy the Quality of Service (QoS) for end users. In this paper, we propose an adaptive CAC method and two different scheduling schemes for multihop WiMAX networks. The proposed CAC in the multihop Base Station (BS) reserves some bandwidth (BW) for the mobile users and changes the BW reservation adaptively based on most recent requests from the handover users. When there are few or no handover users exist in a network, the remaining reserved BW is allocated to low priority Best Effort (BE) users for effective BW utilization. While admitting the New Calls (NCs) or Handover Calls (HCs), the BS verifies both BW and multihop delay requirements to satisfy the QoS of the call. Next, we propose two downlink scheduling algorithms (P+E) and (P+TB) for the BS in multihop networks. The (P+E) scheduler combines the Priority and Earliest Due Date (EDD) scheduling methods, while the (P+TB) scheduler combines the Priority and Token Bucket (TB) scheduling methods. When the network is lightly or moderately loaded, the (P+E) scheduler performs well for both single and multihop users but the performance of real time services are highly affected under high load conditions. On the other hand, the (P+TB) scheduler has very good QoS performance for real time services under high load conditions and also has closer QoS performance to (P+E) scheduler for multihop users under low and moderate load conditions. The simulation results for CAC show that the proposed CAC have lower Call Drop Probability (CDP) for HCs than existing fixed BW reservation policy. The CAC admits more NCs when fewer number of HCs arriving at the BS. The simulation results for scheduling show that the (P+E) scheduler outperforms the (P+TB) scheduler when the system is moderately loaded and the (P+TB) scheduler outperforms the (P+E) scheduler when the system is fully loaded.

Providing strong security is necessary for any wireless access networks. The latest broadband access network implementations are based on WiMAX and LTE, since they support high data rate and mobility. The WiMAX network has well structured QoS mechanisms and security architecture to support all kinds of fixed, mobile and multihop network users. Even though the existing fixed WiMAX network has well defined security architecture, it has many security issues like rouge Base Station (BS), Denial of Service (DoS) and etc. The rouge BS issue was solved in mobile WiMAX network, but the other security issues in fixed WiMAX network and the issues related to mobility like handover latency issues still exist. Most of the existing security issues in fixed and mobile WiMAX networks are solved in the upcoming international mobile telecommunication (IMT) - Advanced WiMAX network. But there are still some security issues due to high mobility support and advanced Medium Access Control (MAC) functionalities. On the other hand, Internet service providers may use the Internet Protocol Security (IPSec) for their wireless access due to its popularity in wired network. But IPSec may affect the throughput performance, since the IPSec header in each packet consumes additional bandwidth. Little research based on real experiments has been reported comparing WiMAX standard security and IPSec. In this paper, the security supported by the standards and IPSec for fixed WiMAX network is evaluated using testbed experiments. From the experimental results and existing research efforts, the security level and QoS support of theoretical and practical security schemes are analyzed.

In this paper, we study the problem of efficiently computing multiple aggregation queries over a data stream. In order to share computation, prior proposals have suggested instantiating certain intermediate aggregates which are then used to generate the final answers for input queries. In this work, we make a number of important contributions aimed at improving the execution and generation of query plans containing intermediate aggregates. These include: (1) a different hashing model, which has low eviction rates, and also allows us to accurately estimate the number of evictions, (2) a comprehensive query execution cost model based on these estimates, (3) an efficient greedy heuristic for constructing good low-cost query plans, (4) provably near-optimal and optimal algorithms for allocating the available memory to aggregates in the query plan when the input data distribution is Zipf-like and Uniform, respectively, and (5) a detailed performance study with real-life IP flow data sets, which show that our multiple aggregates computation techniques consistently outperform the best-known approach.

Integration of cellular users into the peer-to-peer (P2P) network is still in limbo due to limitations caused by heterogeneity, mobility and time-varying capacities of the wireless channel. If traditional Chord is employed to include users from the cellular networks, users under the same base station scatter in logical topology randomly. In this paper, we present a novel cellular Chord (C-Chord) P2P system that integrates the cellular users into the well-established structured P2P network in topology-aware fashion. C-Chord offers the cellular users a choice of downloading contents either from the Internet peers at faster rate or from other cellular users from the same base station avoiding Internet data penalty. We conduct extensive simulations to evaluate the performance of the proposed C-Chord P2P system. The path-length per lookup query is smaller than that of the traditional Chord system. Overhead due to renewal of routing information is also smaller for the cellular users in the C-Chord system. We also measure the throughput at the cellular receivers to analyze the effects of selecting peers either from same base station or from outside the Internet gateway.

Availability of multiple channels and multiple radio interfaces can lead to substantial improvements in the performance of wireless access networks. The optimal allocation of available channels to the users with multiple interfaces however is not a trivial problem especially in a dynamically varying system. In this paper, we will consider the problem of channel and radio interface management in multi-channel multi-interface wireless access networks. In our model, there is a set of orthogonal channels which is shared among several users. Furthermore, each user is equipped with a fixed number of radio interfaces through which it can communicate with the access point. We also consider exogenous stochastic packet arrivals for each user which may be queued for future transmissions. We introduce a general modelling for multi-channel multi-interface wireless access networks for which we propose a throughput optimal channel/interface allocation policy that stabilizes the system for all the arrival rates strictly inside the stability region. We show that the optimal policy determination is equivalent to finding the maximum weighted matching in a bipartite graph at every time slot. Finally, we characterize the stability region for specific cases of the proposed model. Simulation is used to compare the performance of the optimal policy with some other policies in terms of average total queue occupancy.

Prediction of channel characteristics can be of immense value in improving the quality of signals in high frequency satellite systems. Making prediction of rainfall rate (RR) using Markov theory and using that prediction in an intelligent system (IS) to maintain the quality of service (QoS) in channels impacted by attenuation due to weather is the object of this paper. The paper describes the method of prediction rainfall rate using weather collected by environment agencies and applying the predictions to gateway and ground terminal for optimal control of channel characteristics. This novel method of predicting weather characteristics using Markov theory supplies valuable data to develop an enhanced back propagation-learning algorithm to iteratively tune the IS to adapt to changing weather conditions. The effectiveness of the algorithm was tested on a simulated model for activating the weighted modulation and codepoint control. It demonstrated marked improvements in channel parameter tuning and signal quality.

Peer selection strategy is one of the major challenges towards efficient peer-to-peer (P2P) system in wireless mesh networks (WMNs). When peers choose their own utility-maximizing strategies for coalition and peer formation, the solution is always sub-optimal. Peer formation, based on only application layer information, also results in inefficient use of network bandwidth. When multiple recipient-peers try to access the same file from same source-peer simultaneously, contention may occur on the shared wireless channel. On the discovery of multiple source-peers, corresponding recipient-peer may choose optimal source-peer in favor of increased network throughput. Here, we propose a novel optimization method to calculate the upper bound of the aggregate throughput for P2P over WMNs utilizing the underlying physical network information and optimal peer selection strategy. The results show that our favorable-peer selection strategy, results in higher aggregate throughput by selecting optimum source-peers with better load distribution and minimum interference.

We investigate an optimal scheduling problem for a discrete-time system of two parallel queues with infinite capacity, sharing two symmetrical servers. This model can be used to study a variety of scheduling problems in wireless networks. At any time slot, a queue can be served by one or two connected servers; the queue-server connectivity is assumed to be random and modeled by a two-state Markov chain. The arrivals to each queue are assumed to be independent and identically distributed. A scheduled packet completes service successfully with a given probability. Otherwise, it has to be retransmitted in a later time slot. The optimal scheduling policy is defined as the server allocation policy that minimizes, in a stochastic ordering sense, the total number of packets in the system. We prove, using a dynamic coupling method, that a "Most Balancing" policy, a policy that attempts to balance the lengths of the two queues, is optimal. We also compare the performance of the optimal policy to that of a few other policies via simulations.

Physical-Layer Network Coding (PLNC) has recently emerged as a promising new communications paradigm that has the ability to greatly increase the capacity of wireless networks. Current research has also demonstrated that PLNC can decrease the eavesdropping region of an external entity. In this paper we show how it is possible to mitigate passive eavesdropping in the presence of co-located nodes in a PLNC environment.

In this paper, we study the current security standards in multihop WiMAX networks and their security issues. For secured communications, hop-by-hop authentication is necessary for any multihop wireless networks [5][6]. WiMAX multihop networks provide default hop-by-hop authentication in a distributed security mode only. Apart from this, the multihop standards should consider the existing security issues in mobile WiMAX standard [4]. The new multihop standard IEEE 802.16m has improved functionalities and security support. It provides the solution for medium access control (MAC)-control message issues. At the same time, network coding is used for enhanced-multicast broadcast service (E-MBS) retransmission to improve the performance of MBS. However, the standard IEEE 802.16m/D4 fails to consider the security threats for network coding, multihop support and initial ranging. For the above issues, we propose a distributed security architecture using the Elliptic Curve Diffie-Hellman (ECDH) key exchange protocol. Our proposed architecture solves the network coding and other multihop security issues with the help of neighbor authentication/security association (SA), distributed security architecture and ECDH protocol.

Prediction of channel characteristics can be of immense value in improving the quality of signals in high frequency satellite communication channels. Making prediction of rainfall rate (RR) using Markovian theory is the object of this paper. The paper also describes an intelligent system (IS) that uses the predictions made from Markovian model to maintain the Quality of Service (QoS) in channels impacted by rain attenuation (RA). The paper describes the method of prediction of RR using weather correlated database supplied by International Telecommunication Union-Radiocommunications (ITU-R) and applying the predictions to gateway and ground terminal for optimal control of channel characteristics. The proposed method of predicting weather characteristics using Markovian theory supplies valuable data to develop an enhanced back propagation-learning algorithm to iteratively tune the intelligent system to adapt to changing weather conditions. The effectiveness of the algorithm was tested on a simulated model for activating the weighted modulation and codepoint control. It demonstrated marked improvements in channel parameter tuning and signal quality.

The primary concern of broadband wireless technologies is to provide the end-to-end Quality of Service (QoS) for integrated real-time and non real-time applications. The main focus of the IEEE 802.16d/e MAC layer is to manage the radio recourse in an efficient way. The basic functional blocks of the QoS model are addressed by the standards to support five different types of service classes. However, the detailed admission control, radio resource management and scheduling are left for implementation perspective and many research efforts are on going to assure the QoS for end customers. In this paper we propose a hybrid uplink scheduling algorithm (P+E) for subscriber station (SS), which is the combination of priority and Earliest Due Date (EDD) scheduling methods to maintain QoS and utilize the radio resource allocated by the BS in an efficient manner. Simulation results demonstrate the advantages of the proposed hybrid scheduling algorithm.

Appropriate peer selection from the discovered file holders plays a vital role for peer-to-peer (P2P) file sharing over wireless mesh networks (WMNs). When peers choose their own utility-maximizing strategies for coalition and peer formation, the solution is always sub-optimal. Peer formation, based on only application layer information, also results in inefficient use of network bandwidth. When multiple recipient-peers try to access the same file from same source-peer simultaneously, contention may occur on the shared wireless channel. On the discovery of multiple source-peers, corresponding recipient-peer may choose optimal source-peer in favor of increased network throughput. We formulate the joint peer selection and utility maximization problem as a mixed integer nonlinear programming (MINLP) framework. We also propose penalty-based heuristic genetic algorithm (GA) to solve the MINLP. The results show that our favorable-peer selection strategy results in higher aggregate throughput by selecting optimum source-peers with better load distribution and minimum interference.

Device-to-device (D2D) communication as an underlaying cellular network empowers user-driven rich multimedia applications and also has proven to be network efficient offloading eNodeB traffic. However, D2D transmitters may cause significant amount of interference to the primary cellular network when radio resources are shared between them. During the downlink (DL) phase, primary cell UE (user equipment) may suffer from interference by the D2D transmitter. On the other hand, the immobile eNodeB is the victim of interference by the D2D transmitter during the uplink (UL) phase when radio resources are allocated randomly. Such interference can be avoided otherwise diminish if radio resource allocated intelligently with the coordination from the eNodeB. In this paper, we formulate the problem of radio resource allocation to the D2D communications as a mixed integer nonlinear programming (MINLP). Such an optimization problem is notoriously hard to solve within fast scheduling period of the Long Term Evolution (LTE) network. We therefore propose an alternative greedy heuristic algorithm that can lessen interference to the primary cellular network utilizing channel gain information. We also perform extensive simulation to prove the efficacy of the proposed algorithm.

In mobile ad hoc networks (MANETs), hierarchical key management structure has some distinct features and becomes popular in many applications. In a MANET where security requirement is high, node states should be considered when constructing a private key generator (PKG). In this paper, we propose a distributed hierarchical key management scheme in which nodes can get their keys updated from optimally selected nodes. The key management problem is formulated as a stochastic system, and the proposed scheme can select the best nodes from all available ones based on their security conditions. Simulation results show that the network compromising probability in the proposed scheme can be decreased significantly.

Nodes in disruption-tolerant networks (DTNs) usually exhibit repetitive motions. Several recently proposed DTN routing algorithms have utilized the DTNs' cyclic properties for predicting future forwarding. The prediction is based on metrics abstracted from nodes' contact history. However, the robustness of the encounter prediction becomes vital for DTN routing since malicious nodes can provide forged metrics or follow sophisticated mobility patterns to attract packets and gain a significant advantage in encounter prediction. In this paper, we examine the impact of the blackhole attack and its variations in DTN routing. We introduce the concept of encounter tickets to secure the evidence of each contact. In our scheme, nodes adopt a unique way of interpreting the contact history by making observations based on the collected encounter tickets. Then, following the Dempster-Shafer theory, nodes form trust and confidence opinions towards the competency of each encountered forwarding node. Extensive real-trace-driven simulation results are presented to support the effectiveness of our system.

In this paper, we develop a framework for achieving scalable and communication-efficient dissemination of content in pub/sub systems. To maximize communication sharing across subscriptions, our routing framework groups subscriptions based on similarity, and transmits content matching one or more subscriptions in a group over a single dissemination tree for the group. We develop a cost model that uses published content samples in conjunction with the knowledge of consumer subscriptions to estimate the communication cost of a set of routing trees for subscription groups. The problem of computing a communication-optimal set of routing trees is then formulated as an optimization problem that seeks to find trees with the minimum cost. It turns out that the problem of computing a minimum-cost tree for a subscription group is a new generalization of the well-known Steiner tree problem, and an interesting problem in its own right. We develop an approximation algorithm that uses low-stretch spanning trees to compute a tree whose communication cost is within a polylogarithmic factor of the optimum. We use this to compute trees for various subscription- grouping configurations generated using a greedy clustering strategy, and select the one with the lowest cost. Our experimental study demonstrates the effectiveness of our content-aware routing approach compared to traditional routing based on content oblivious spanning trees.

Rain, snow, gaseous, cloud, fog, scintillation and other atmospheric properties can have a distorting effect on signal fidelity of Ku and Ka bands, thus resulting in excessive digital transmission error. This loss of signal is commonly referred to as signal attenuation. Signal attenuation impacts the QoS in wireless and satellite networks. Accurately predicting channel attenuation due to atmospheric conditions can enable mitigation planning by adaptively selecting appropriate modulation, coding, transmitted power level, transmission rate and configured frame size. The aim of this paper is to estimate different attenuations using predicted signal-weather correlated database in collaboration with ITU-R propagation models combined with interpolation methods, gateway, and ground terminal characteristics. A three dimensional relationship is proposed among these attenuations with respect to propagation angle and rainfall rate [l]-[8]. The outcome is key factor in diagnosing, adjusting and improving satellite signal power, modulation and coding schemes, monitored and controlled altogether by a powerful and efficient intelligent-based attenuation countermeasure system. These results will lead to an enhanced back propagation-learning algorithm that is used to iteratively tune the IS with returned SNR values to activate the weighted Modulation/Codepoint to its optimal values, depending on actual or predicted weather conditions, configuration settings and tolerance/safety margins for SLA commitment.

Many structured peer-to-peer (P2P) systems have been proposed as distributed hash tables (DHTs) for fast and efficient lookup of queries. In this paper, we propose a novel technique for improving average lookup times in P2P systems by caching additional neighbor pointers based on peer access frequencies. In particular, we address the problem of each peer choosing the k best pointers to store (in addition to its index pointers) to minimize the average query lookup times. We focus on two popular P2P systems, namely Pastry and Chord: we exploit the inherent structure of these systems to develop efficient, scalable algorithms for optimally choosing the k additional pointers. Simulations with Chord and Pastry demonstrate that our algorithms are very effective in reducing the lookup times significantly. Our approach can be used in tandem with other techniques such as item caching and replication, and is particularly useful for applications such as name services in mobile environments or location services, where we can expect a low churn rate for peers and a relatively higher churn rate for items.

Weather attenuations can have a distorting effect on signal fidelity above 10 GHz that lead to excessive digital transmission error. This loss of signal is commonly referred to as signal attenuation. Signal attenuation impacts QoS in wireless and satellite networks. An intelligent decision support system is therefore necessary for service providers by accurately calculating rain, gaseous, cloud, fog, and scintillation attenuations using predicted signal-weather correlated database in collaboration with ITU-R propagation models combined with gateway, and ground terminal characteristics. The effect becomes a key feature in adjusting and improving satellite signal power, modulation and coding schemes, monitored and controlled altogether by a powerful and efficient intelligent-based attenuation countermeasure system. A three dimensional relationship is proposed among these attenuations with respect to propagation angle and rainfall rate (Harb et al., 2007). The result pilots an enhanced back propagation-learning algorithm that is used to iteratively tune the intelligent controller based on fuzzy logic technique with returned SNR values for activating the weighted Modulation/Codepoint to its optimal values, depending on actual or predicted weather conditions, configuration settings and tolerance/safety margins for SLA commitment.

This paper describes a unification of two different SQL extensions for streams and its associated semantics. We use the data models from Oracle and StreamBase as our examples. Oracle uses a time-based execution model while StreamBase uses a tuple-based execution model. Time-based execution provides a way to model simultaneity while tuple-based execution provides a way to react to primitive events as soon as they are seen by the system. The result is a new model that gives the user control over the granularity at which one can express simultaneity. Of course, it is possible to ignore simultaneity altogether. The proposed model captures ordering and simultaneity through partial orders on batches of tuples. The batching and the ordering are encapsulated in and can be modified by means of a powerful new operator that we call SPREAD. This paper describes the semantics of SPREAD and gives several examples of its use.

Most wireless ad hoc networks research assumes a common communication channel. Using multiple channels can increase network capacity by transmitting traffic on different channels in an interference area. Channel assignment is a critical issue for the multi-channel scheme. Proactive receiver-based channel assignment (RCA) which is a network layer multichannel solution has shown better performance compared to single common channel solutions. However, channel collision cannot be resolved in some scenarios and a large number of orthogonal channels are needed with the RCA scheme. This paper proposes an on-demand negotiation-based channel assignment (NCA) that determines the communicating channel using the network topology and the dynamic traffic. We extend the OLSR (optimized link state routing) protocol to support NCA. Simulation results with NS-2 indicate considerable performance improvement on throughput and end-to-end delay of NCA over RCA for most scenarios.

Rain and snow can have a distorting effect on Ku and Ka bands signal fidelity resulting in excessive digital transmission errors. This loss of signal attenuation is commonly referred to as rain fade. Rain fade impacts the Quality of Service in wireless and satellite networks. A decision support system is therefore necessary for service providers to accurately predict rain fade and establish mitigation planning by adaptively selecting appropriate power level, coding and modulation schemes. This paper establishes an important component of the decision support system by adaptively computing rainfall rate and rain attenuation at any location on earth using ITU-R models combined with bi-linear interpolation and frequency extrapolation. We also introduce a novel method for accurately determining rain attenuation as a function of frequency based on proceeding results from prediction weather database, since rain attenuation is considered a dominant impairment for wireless signals [1]–[6]. Finally, a three dimensional relationship is proposed for rain attenuation with both frequency and probability to provide decision support system with an accurate view of satellite’s parameters. The derived parameter values, being fed through neural networks and fuzzy systems to improve estimate Signal to Noise Ratio, will enable the decision support system to maintain Quality of Service and Service Level Agreements by adaptively adjusting satellite signal power, modulation, coding, and data rate at unpredictable weather conditions.

We propose two versions of Link Failure Probability (LFP) based backup resource sharing algorithms, namely LFP based First-Fit algorithm, and LFP based Best-Fit algorithm for Generalized Multi-Protocol Label Switching networks. Customers' availability requirements are met by adjusting the availability of the protection paths with different sharing options. Information required for calculating the availability of both the working, and protection paths can be collected along the specific working, and protection paths, thus avoiding the requirement for flooding. This makes our algorithms scalable for a large network. Our algorithms work consistently against both single, and multiple failures. Furthermore, we propose extensions for the existing signaling protocols to demonstrate that our proposed algorithms require minimum changes to the existing protocols. Simulation results show that our proposal performs better than the conventional Dedicated Path Protection schemes in terms of Call Acceptance Rate, and Total Bandwidth Consumption. Finally, by comparing simulation results to analytical results for a simplified network, we provide some insights into the correctness, and efficiency of our proposed algorithms

Recently, there has been a growing interest in gossip-based protocols that employ randomized communication to ensure robust information dissemination. In this paper, we present a novel gossip-based scheme using which all the nodes in an n-node overlay network can compute the common aggregates of MIN, MAX, SUM, AVERAGE, and RANK of their values using O(n log log n) messages within O(log n log log n) rounds of communication. To the best of our knowledge, ours is the first result that shows how to compute these aggregates with high probability using only O(n log log n) messages. In contrast, the best known gossip-based algorithm for computing these aggregates requires O(nlog n) messages and O(log n) rounds. Thus, our algorithm allows system designers to trade off a small increase in round complexity with a significant reduction in message complexity. This can lead to dramatically lower network congestion and longer node lifetimes in wireless and sensor networks, where channel bandwidth and battery life are severely constrained.

In this paper, we consider fair scheduling of soft real-time applications on multiprocessors using the earliest pseudo deadline first (EPDF) Pfair algorithm. Our main contributions are twofold. First, we establish a condition for ensuring a tardiness of at most one quantum under EPDF. This condition is very liberal and should often hold in practice. Second, we present simulation results involving randomly-generated task sets, including those that do not satisfy our condition. In these experiments, deadline misses were rare, and no misses by more than one quantum ever occurred.

In prior work on multiprocessor fairness, efficient techniques with provable properties for reallocating spare processing capacity have been elusive. In this paper, we address this shortcoming by proposing a new notion of multiprocessor fairness, called quick-release fair (QRfair) scheduling. Under QRfair scheduling, each task is specified by giving both a minimum and a maximum weight (i.e., processor share). The goal is to schedule each task (as the spare capacity changes) at a rate that is (i) at least that implied by its minimum weight and (ii) at most that implied by its maximum weight. We present a quick-release variant of the PD/sup 2/ Pfair scheduling algorithm called PD/sup Q/ and prove that the allocations of PD/sup Q/ always satisfy (i) and (ii). Also, we present results from simulation experiments that show the efficacy of PD/sup Q/.

We propose two server implementations for multiplexing aperiodic and recurrent real-time tasks in fair-scheduled multiprocessor systems. We also provide admission-control tests for scheduling hard aperiodic tasks. Further, we consider several complexities, most of which arise because of the parallelism available in multiprocessor systems, and present techniques to handle them. Finally, we present experimental results that demonstrate the effectiveness of our implementations.

The demand for continuous service in mission- and safety-critical software applications is increasing. For these applications, it is unacceptable to shutdown and restart the system during software upgrade. This paper examines issues relating to on-line upgrades for mission- and safety-critical software applications. We believe that a dynamic architecture and communication model provides an excellent foundation for runtime software evolution. To solve the problems mentioned above, we designed and implemented a framework, which addresses four main areas: dynamic architecture and communication model, reconfiguration management, the upgrade protocol, and the upgrade technique. The framework can be used for online upgrading of multi-task software applications, which provide multiple mission-critical services. In the framework discussed in the paper, the ability to make runtime modifications is considered at the software architecture-level. The dynamic architecture and communication model makes it possible for software applications to add, remove, and hot swap modules on the fly. The transition scenario is specified by the upgrade protocol. The framework also provides the mechanism for maintaining state consistency. In order to ensure a reliable upgrade, a two-phase commit protocol is utilized to implement the atomic upgrade transactions. In addition, a command line interface facilitates the reconfiguration management. A simulation study of the proposed framework was carried out for live software upgrade of several practical applications. The results of the simulation are also presented.

The PD2 Pfair/ERfair scheduling algorithm is the most efficient known algorithm for optimally scheduling periodic tasks on multiprocessors. In this paper, we prove that PD2 is also optimal for scheduling "rate-based" tasks whose processing steps may be highly jittered. The rate-based task model we consider generalizes the widely-studied sporadic task model.

In this paper, we prove that a simplified variant of the PD Pfair algorithm, called PD/sup 2/, is optimal for scheduling any mix of early-release and non-early-release asynchronous tasks on a multiprocessor. This result breaks new ground by incorporating both early-release and non-early-release tasks under a common framework. In addition, all prior work on optimal multiprocessor Pfair scheduling algorithms has been limited to synchronous periodic task systems.

Presents a variant of Pfair scheduling (S. Baruah et al., 1995, 1996), which we call early-release fair (ERfair) scheduling. Like conventional Pfair scheduling, ERfair scheduling algorithms can be applied to optimally schedule periodic tasks on a multiprocessor system in polynomial time. However, ERfair scheduling differs from Pfair scheduling in that it is work-conserving. As a result, average job response times may be much lower under ERfair scheduling than under Pfair scheduling, particularly in lightly loaded systems. In addition, run-time costs are lower under ERfair scheduling.