There is a need to ensure unconditionally secure communications between different sites of an organization. We use quantum key distribution (QKD) protocol to provide a continuous stream of secret key bits to each communicating pair for message encryption through one-time-pad (OTP) cryptography. Due to long distance between different sites, trusted nodes are used to relay each service key in a hop-by-hop manner from one end node to another end node of a communicating pair. In a QKD network, routes for key relaying can be affected by availability of relay key bits at trusted nodes. Also, relay key allocation among different routes can impact security. We consider the scenario of supporting multiple communicating pairs, where each pair demands delivery of a certain service key rate across the QKD network, and trusted nodes may not have sufficient relay key rates to perform bitwise encryption to protect the service key. Hence, there is a need to allocate the limited relay key bits to meet all service key delivery demands while considering its effects on security. We propose to perform jointly routing and relay key allocation to minimize attack success probability. We have formulated the joint problem as an optimization and further proposed an efficient algorithm to find the optimal solutions. We have evaluated the proposed algorithm to confirm its ability and efficiency in finding optimal routes and relay key allocations. For the specific network topology that we have adopted, results show that the minimum number of required trusted nodes increases linearly when end nodes are added to the system. Furthermore, we can achieve a higher security level by adding more trusted nodes in a QKD network. But increasing the number of trusted nodes beyond the minimum requirement may not continue to reduce significantly the attack success probability.

Before the world-wide deployment of autonomous vehicles, it is essential to implement intermediate solutions with partial autonomy. One such solution is the use of vehicle teleoperation, the act of controlling a vehicle from a distance. In real time applications of teleoperation, it is often pertinent to use augmented reality components within the teleoperator view, which are referred to as a predictive display. In this work, we evaluate our predictive display method, which is a guiding path based on the free space in the environment. The path is generated based on our Dual Transformer Network (DTNet), which uses both object detection and lane semantic segmentation to define the free space in the environment. While the model has previously performed well on image data, it is necessary to observe its accuracy in the presence of time delay and packet loss, to assess its performance in a real-time setting. Thus, in this work, we use CARLA simulator to compare the detected free space on the teleoperator side to the true free space on the vehicle side across different values of time delay and packet loss. Under optimal network conditions, our model yielded a remarkable 87.9% DSC score and 81.3% IoU score. Defining our minimum performance threshold as 80% DSC and 70% IoU, we conclude that our model can effectively mitigate the challenges of time delay below 100ms and packet loss below 1%, both of which represent substantial tolerances.

Cyber–physical systems rely heavily on communication networks for remote monitoring and control. It is crucial to protect the communication networks from cyberattacks because an attack on the physical subsystem can be indirectly launched from a compromised cyber subsystem. Since remote control devices have limited computational power, we ensure communication confidentiality and integrity using one-time-pad (OTP) symmetric cryptography, which despite simple is unconditionally secure. To provide OTP with secret keys, we use quantum key distribution (QKD) across multiple hops, where each intermediate relay is a trusted node. These nodes can be weak points in cyberattacks. Hence, this article focuses on routing in multihop QKD networks that reduces the required number of trusted nodes. We formulate and solve an optimization problem to find the set of QKD routes that minimizes the number of activated trusted nodes while satisfying the secret key rate requirements of multiple communicating pairs. Extensive evaluation results confirm that the proposed scheme can indeed has fewer activated trusted nodes as compared to a benchmark scheme that finds only the shortest paths for communicating pairs.

In a cyber–physical system, quantum key distribution (QKD) protocols can provide a continuous supply of common secret key bits for secure communications between the control center and a remote device. QKD protocols operate on a peer-to-peer basis between two adjacent nodes and are distance-limited. Hence, trusted nodes are installed between two communicating end nodes for a better QKD range and key rate. These trusted nodes relay in a hop-by-hop manner, key bits generated in the first hop to the other end node. At each trusted node, the first hop key bits are encrypted by other locally generated key bits before being relayed. Since QKD process is stochastic, secret key bits are generated at different rates at different hops. Thus, buffer is needed at a trusted node to temporally hold some key bits while waiting for other key bits. There is no existing work that accounts for such a realistic relaying operation in deriving the key rate. This article contributes to developing a key rate model to determine accurately the end-to-end rates across multiple trusted nodes. We have evaluated accuracy of the proposed model through extensive simulations. The results show that there exist an optimal number of trusted nodes for a given distance between two end nodes. For example, the optimal number of relays increases from four for 100 km to six for 200 km.

We use symmetric cryptography for secure communications with resource-limited smart grid control devices. We propose the novel idea of using the unmanned aerial vehicle (UAV) as a physical courier to carry secret key bits generated at the control center to remote control devices. While distributing secret keys, the UAV may be attacked in an attempt to sabotage secure communications. The UAV may fly a longer route to avoid attackers but it has a limited onboard battery capacity and must visit each device within a time limit to prevent a secret key deficit. We formulate an optimization to find the lowest attack risk flight route for secret key distribution while taking into consideration key deficiency and battery capacity. Such optimization is NP-hard. We further propose an efficient algorithm to find a low-risk flight route in less than a second, even for a large power grid system with more than a hundred nodes. For large systems, we modify the proposed algorithm to find a low-risk flight route as well as to determine the required UAV flight duration and battery size. Extensive simulation results confirm the superiority of the proposed algorithm against a baseline scheme that is ignorant of attackers.

With increasing distributed energy resource integration, future power and energy systems will be more decentralized using advanced Internet of Things (IoT) technologies. Integrated energy systems (IESs) boost the whole energy efficiency by coordinating multiregional energy resources and networks. However, distributed coordination of the IES requires different subregions or energy hubs (EHs) to share their sensitive information (e.g., energy demands and operation status) explicitly, which poses serious privacy leakage. To this end, secure multiparty computation (SMPC) is innovatively introduced to the distributed optimization of the IES in this article. First, the standardized modeling of multiple interconnected EHs with the linearized network models is formulated to analyze the IES’s inherent energy and information interaction comprehensively. Then, a privacy-preserving distributed optimal energy flow algorithm is proposed by combining the Paillier Cryptosystem mechanism with the alternating direction multiplier method (ADMM). Theoretical analysis proves the proposed method is convergent without sharing sensitive information in plaintext. Numerical experiments on a three-subregions IES validate that the proposed method has better convergence performance than the differential privacy-based method. Results show that the maximum relative error of the distributed optimal solutions with various step sizes is no more than 0.072% compared with the centralized method.

An increasing number of distributed energy resources (DERs), such as rooftop photovoltaic (PV), electric vehicles (EVs), and distributed energy storage, are being integrated into the distribution systems. The rise of DERs has come hand-in-hand with large amounts of data generated and explosive growth in data collection, communication, and control devices. In addition, a massive number of consumers are involved in the interaction with the power grid to provide flexibility. Electricity consumers, power networks, and communication networks are three main parts of the distribution systems, which are deeply coupled. In this sense, smart distribution systems can be essentially viewed as cyber–physical–social systems. So far, extensive works have been conducted on the intersection of cyber, physical, and social aspects in distribution systems. These works involve two or three of the cyber, physical, and social aspects. Having a better understanding of how the three aspects are coupled can help to better model, monitor, control, and operate future smart distribution systems. In this regard, this article provides a comprehensive review of the coupling relationships among the cyber, physical, and social aspects of distribution systems. Remarkably, several emerging topics that challenge future cyber–physical–social distribution systems, including applications of 5G communication, the impact of COVID-19, and data privacy issues, are discussed. This article also envisions several future research directions or challenges regarding cyber–physical–social distribution systems.

Internet of Things (IoT) has facilitated the emergence of various applications which require deploying a large number of sensors over a wide geographical area. For efficient communications, sensors with similar data within a vicinity are grouped into clusters. Compared to centralized sensor clustering, a distributed scheme is more scalable, can avoid traffic congestion, and does not suffer from single-point failure. However, due to a lack of global information, distributed sensor clustering may create more clusters than a centralized scheme. In this article, we propose to use an artificial neural network (ANN) as a tool to summarize the experience of a centralized clustering scheme in the presence of global information. Then, this experience becomes a learned knowledge to be transferred to distributed decision makers, which may subsequently approximate the centralized scheme in making the clustering decision even with access to only local information. To achieve the desired performance, we derive some secondary local information from original local information, and use it as input to ANNs to compensate for the loss of global information. Evaluation results show that it is feasible in achieving at a distributed decision maker, a same clustering solution as the centralized scheme, with about 5% clustering error probability.

As an Internet of Things (IoT) application in the smart grid, dynamic thermal rating (DTR) requires real-time measurement of conductor temperature from field sensors that are installed at remote transmission lines. For such IoT-based transmission line monitoring, we need a robust communication network. This article proposes to group sensors with similar measurement characteristics into a cluster such that each member can accurately represent the entire cluster. Then, communication robustness can be achieved by establishing multiple routes to the control center, where each route may originate from a different member in the cluster. First, we formulate a global constrained optimization for sensor clustering. We use the optimization solutions to train a set of artificial neural networks (ANNs), where each ANN is deployed to make a local decision at one sensor. Specifically, we propose the novel usage of ANN as a tool to transfer knowledge from a global decision maker to a set of local decision makers. Evaluation results show that there remains a noticeable knowledge gap between global and local decision makers, where in average, the global decision maker and an ANN make an identical decision in only about 70% of the times. Despite this less than ideal success probability, the number of clusters produced by the ANN-assisted local scheme is only 1.9 more than that by the global scheme.

We explore the use of software-defined networking (SDN) technology in building a communication network for smart grid. With cyber-physical interdependence, such communication network may suffer from cross-network cascading failures. To prevent the failures, we perform virtual network function (VNF) orchestration jointly with power-disjoint routing. Our work is novel in proposing an efficient scheme to find power-disjoint routes at the same time of performing VNF orchestration. We formulate an optimization to maximize the ratio of power-disjoint route count to VNF orchestration cost. The optimization has a non-linear non-convex objective function. We propose a two-level hierarchical solution approach. At higher level, the scheme converts the problem into a fractional maximum flow circulation, which can be solved using simplex method to find the maximum number of power-disjoint routes. Given a higher level solution, the lower level aims to minimize the VNF orchestration cost while satisfying VNF chaining and placement requirements. This lower level hierarchy uses the Dijkstra’s algorithm in building a sequence of minimum spanning trees, each roots at the current VNF hosting node in a VNF chain. Extensive simulation results confirm that the proposed scheme can find the maximum number of power-disjoint routes and minimize the cost within a second, for a system with 120 communication nodes. The results show that the number of power-disjoint routes can be increased by increasing either the number of nodes or node degree, but only the node degree can keep the cost flat. Therefore, one should build a robust software-defined smart grid communication network by enhancing node connectivity.

Community smart grid is formed by a group of neighboring households to share renewable generators and energy storage facilities. Within a community grid, all power grid entities are connected to power lines that are downstream to a common substation. In this paper, we use device-to-device communications to connect sensors that are installed at grid entities to their respective control units. The topology and node membership of such communication network depend on the topology of its power grid. As such, a communication node may not be assigned the best quality channel. This has imposed additional constraints in radio resource allocation. We exploit the feature that sensors and control units are static but cellular users are mobile, in proposing a two-stage radio resource allocation scheme. In the planning stage, we use the Hungarian method to find the optimal channel assignment for static sensors and control units. In the operation stage, we run recursively the Hungarian algorithm to allocate proportionally all remaining channels to cellular users. Given the channel assignment, the operation stage further performs transmit power allocation to all nodes. The power control problem is originally nonconvex. We transform the problem into a difference of convex structure, which can be solved successively. We have evaluated the proposed radio resource allocation scheme through extensive simulations. Results confirm that the scheme is indeed efficient in assigning channels and finding the minimum transmit power, to maximize sum-rate of cellular users while guaranteeing a minimum throughput to each sensor and control unit.

This study aims to optimize the design and performance of three-dimensional (3D) underwater acoustic sensor networks (UASNs). First, we develop an analytical model to quantify network performances in terms of the packet queueing delay and packet error probability for sensors in a 3D UASN. The model considers the retransmission delay due to packet transmission errors and packet collisions when calculating the packet queueing delay. The packet queueing delay depends on the choice of medium access control (MAC) protocol. We consider two different MAC protocols: slotted ALOHA and Request-to-Send and Clear-to-Send (RTS/CTS)-based MAC, which are the representative random access-based and handshake-based MAC protocols for UASNs, respectively. Based on the model, we further determine the smallest data sink density required to meet the desired packet error probability requirement for underwater sensor density, which can help network operators to design and build UASNs in a cost-effective way. To do this, we formulate a simple optimization problem that aims to minimize the data sink density while guaranteeing an upper bound for packet error probability. Using extensive numerical evaluations, network operation strategies are then presented to achieve the desired performance requirements in 3D UASNs.

In smart grid, power grid and communication network are interdependent. With this interdependence, a failure in one network may lead to a cascade of failures across the networks. Considering such failures, we develop a model to determine communication route failure probability and quantify its impact in term of lost load. We formulate an optimization to find the set of optimal routes that minimize the impact triggered by an initial route failure. Unfortunately, the optimization is NP-hard and relies on a non-trivial algorithm to calculate the amount of lost load. We further transform the optimization into a dynamic programming problem using the Bellman's optimality equation. We propose a Gauss-Seidel value iteration algorithm to solve the dynamic programming problem. Simulation results confirm that the proposed algorithm can accurately find the set of optimal routes. For a network configuration with 7 power nodes and 22 routers, the algorithm can efficiently find optimal routes in 2.4 seconds while solving the original optimization takes more than 48 hours.

Smart grid is a cyber-physical system with interdependent power grid and communication network. Such interdependence make the smart grid fragile against cascading failures, where an initial failure in communication network may lead to further failures in power grid, and vice versa. We prevent such inter-network cascading failure by stopping an initial failure from propagating. This is achieved by providing a sufficient number of power-disjoint communication routes between power nodes and control center. The number of power-disjoint routes is a robustness metric. We aim to maximize robustness by configuring the interdependence relationship between power grid and communication networks. Such relationship indicates which power node supplies energy to which communication node, and which communication route is used to connect which power node to the control center. Following Menger's Theorem, we transform such configuration problem into a Maxflow problem and solve it using the simplex algorithm. We have evaluated the proposed method through extensive simulations. The results confirm the optimality and computational efficiency of the proposed method. The number of power-disjoint routes increases with an increase in the network size, but can never exceed the number of node-disjoint routes for a same network.

With the integration of distributed generations into smart grid, energy storage units (ESUs) are deployed to absorb excessive fluctuation in power flow. Data must be collected from sensors when making ESU charging and discharging decisions. However, existing ESU management schemes have not considered this need of sending data over realistic communication channels with packet errors. This paper proposes a distributed ESU management scheme that can operate reliably over error-prone wireless communication channels. The proposed scheme uses the Markov decision process to make local decision at each ESU, and aims to minimize power loss while keeping the voltage violation probability below an acceptable level. The scheme has been evaluated through extensive simulations. Results confirm that the scheme can operate efficiently over impaired communication channels. Power losses are reduced by up to 50% compared to a naive centralized scheme while maintaining the voltage violation probability below 0.005.

Efficient demand side management through dynamic power pricing is an important application in the smart grids. However, in the absence of a detailed user consumption model, it is difficult to set an optimal power price. In this paper, we propose to efficiently capture the user consumption behavior through a user-dependent acceptance price. Each rational user will decide its own acceptance price based on its desire to get served. Then, we model the selfish interaction between operator and users as a Stackelberg game, where the operator aims to maximize its profit, while the individual users try to pay the lowest price and be served in time. After each user selfishly declares its own acceptance price, the operator sets an optimal power price, based on the user feedback and taking into account the random output of the renewable power sources. Simulation results confirm that the operator can maximize its profit and the users get served in time, while the proposed scheme leads to the optimal usage of the renewable power production.

HetNet is a cost-efficient way to increase network capacity to support rapidly increasing data traffic. In HetNets, it is desirable to ensure that the packet delay as experienced by a user is acceptable to an application. This paper focuses on finding the packet queueing delay of a mobile user in HetNets. We develop a simple two-dimensional finite state Markov chain model to represent the queue size and data rate of a mobile user. By solving the Markov chain for its stationary state probability distribution, we can determine the average packet delay as a function of traffic arrival rate. We have verified the numerical model against results from simulations. By using the model, we can find the suitable femto cell density to achieve a desired packet delay.

Coverage of a camera sensor network (CSN) is a critical issue in deploying such network in maritime environment. In such environment, camera sensors will not be stationary after the initial deployment due to the hostile sea environment. Hence, the mobility pattern poses a major limitation on identifying the time-varying coverage. In full-view coverage, target's facing direction has been introduced to judge whether a target's facing direction is guaranteed to be captured. To this end, we exploit full-view coverage in CSN, since image shots at the frontal viewpoint of a given target considerably increase the possibility to detect and recognize the target. In this paper, we have developed a mobility pattern based on wind speed and spring relaxation technique which are used to characterize the total displacement of a given buoy. Furthermore, the average percentage of full-view coverage has been evaluated based on different parameters such as equilateral triangle grid length, sensing radius of camera, wind speed and wave height. Consequently, the proposed model has been validated through MATLAB simulation platform.

Heterogeneous cellular networks can improve network capacity by co-deployment of macro and femto base stations (BSs). The capacity improvement comes with a higher power consumption. This paper proposes a method to minimize the power consumption without compromising the quality-of-service demand which is measured in terms of packet delay. First, we derive a closed-form expression for the packet delay as a function of macro and femto BS densities. Then, we determine the BS densities that minimize the network power consumption under a packet delay constraint. Evaluation results show that heterogeneous networks always outperforms a homogeneous network in terms of power-delay characteristics. With the optimal BS densities for a given packet delay requirement, the minimum power consumption of a heterogeneous network is always lower than that of a homogeneous network.

This paper proposes a Markov decision process (MDP) based base station management scheme that dynamically and collectively manages activation of a group of base stations depending on the time-varying traffic demand for power conservation in self-organization networks. Our MDP model is unique in a sense that it accurately captures the dynamics of handover traffic among neighboring cells, and it formulates infeasible actions as constraints in a constrained optimization problem. Simulation results confirm that the proposed scheme can significantly reduce power consumption: 55% of daily power savings, upto 73% of power savings during low traffic periods, and the minimum 23% of power savings even during high traffic periods. Our MDP algorithms find desired optimal policies to deactivate unnecessary base stations without sacrificing network performances.

With increasing awareness toward protecting our environment, this paper intends to reduce the CO2 emission of a wireless cellular network by reducing the power consumption of its base station. We propose to reduce power consumption by dynamically activating and deactivating the modular resources at the base station depending on the instantaneous network traffic. In order to achieve the objective, we develop a discrete time Markov Decision Process (DTMDP) to capture the dynamics of the system. In the DTMDP, the action to be taken at each decision epoch is to activate a new resource module, to deactivate a currently active resource module, or to stay the same. We further develop a linear programming approach to solve the DTMDP for optimal probabilistic decision policy. Evaluation results show that the optimal probabilistic policy for resource activation can reduce power consumption for more 50 percent under various traffic load conditions, without compromising network service quality which is measured in terms of user blocking probability.

Recently, the issue of energy efficiency in wireless networks has attracted much research attention due to the growing concern on global warming and operator's profitability. We focus on energy efficiency of base stations because they account for 80% of total energy consumed in a wireless network. In this paper, we intend to reduce energy consumption of a base station by dynamically activating and deactivating the modular resources at the base station depending on the instantaneous network traffic. We propose an online reinforcement learning algorithm that will continuously adapt to the changing network traffic in deciding which action to take to maximize energy saving. As an online algorithm, the proposed scheme does not require a separate training phase and can be deployed immediately. Simulation results have confirmed that the proposed algorithm can achieve more than 50% energy saving without compromising network service quality which is measured in terms of user blocking probability.

Wireless personal area network (WPAN) technology will be used for cable replacement in connecting various devices and sensors carried by a person for health monitoring. With the increasing need, every person will eventually have a WPAN and each WPAN is an autonomous entity. When two WPANs come into the radio range of each other, a collision occurs and network performance is affected. To manage the impact, the WPAN collision must be detected early and resolved quickly. This paper assumes the use of IEEE 802.15.4 WPAN. Then, we propose a MAC scheme, called Inter-Network Collision Avoidance (INCA) to detect and avoid WPAN collision accurately in a distributed manner. The proposed INCA scheme does not require any central coordinator for transmission scheduling. Instead, INCA successively separates each pair of colliding WPANs after identifying which portion of an active period suffers from the collision. We have evaluated the proposed scheme through extensive simulations. Evaluation results confirm that WPAN collisions can be effectively resolved leading to a significantly higher normalized throughput. Specifically, the probability of suffering from zero normalized throughput can be reduced from about 40% to less than 1%.

Smart grid has emerged in our fight against global warming by integrating renewable power sources into electrical power transmission network. We use dynamic pricing to control power demand in respond to the fluctuation in renewable power output. In dynamic pricing, the operator needs to collect information about power supply and to broadcast the latest power price. This information exchange is done through the wireless communication network within the smart grid. Wireless transmissions are error-prone and transmission errors will result in a loss of precision in demand control, which will further lead to a loss of profit to the operator. In view of the problem, this paper proposes a cooperative wireless transmission scheme called Cooperative Dissemination of Power Price and Supply (CDPS) for smart grid. The scheme exploits broadcast nature of radio channel to improve efficiency in delivering power prices to all customers, and in collecting power supply information from all renewable power sources. In CDPS, a customer that has overheard transmitted power supply information from its neighbors may help in delivering the information to the operator. Similarly, a customer that has received the latest power price may cooperatively retransmit the information to its neighbors that have not received the information. We have evaluated the performance of CDPS through random event simulations. The simulation results confirm that CDPS can indeed improve the operator's profit through more effective dissemination of information. Also, CDPS can help in reducing the amount of renewable power wasted due to a loss of reported information.

Nowadays, accurate and low-cost autonomous maritime surveillance of camera sensor network is a critical requirement for various applications. In a maritime environment, camera sensors are deployed on mobile platforms, such as buoys. With an anchored buoy architecture, sensor locations are quasi-stationary. When sensors move, some areas may not be covered at some times. This paper analyzes the extend of the uncovered area in a realistic maritime environment. We present numerical results to variation in uncovered areas from time to time. Also in this paper, the simulation of the uncovered area detection of camera sensor network (CSN) used in maritime surveillance is presented using MATLAB.

In the literature, cooperative relaying and network coding have been used separately in improving performance of wireless MAC protocols. In this paper, we propose a novel scheme that combines both cooperative relaying and network coding for further performance improvement. The proposed scheme considers two challenges of network-coded cooperative MAC operating in a realistic wireless network. First, links in realistic networks inherently operate with different data rates due to varying channel conditions and distances between the nodes. Existing works do not consider this issue and consequently the coding advantage is not fully harnessed. In our proposed scheme, we integrate both network coding and multi-rate issues as a single optimization problem. Second, network coding used in existing works require costly and reliable feedback in order to harness the gain. Since realistic links are unreliable in nature, our proposed scheme uses a cyclic coding method instead of the traditional XOR coding. Our results show that the proposed scheme can achieve a gain that is two times greater than a non-cooperative scheme.

Implementing incremental relaying in a practical system is not a trivial task because it requires the destination node to provide feedback on success or failure of a transmission. In practice, the feedback may be affected by propagation impairments and collisions. In this case, the relay and the source should coordinate among themselves in the absence of perfect feedback information such that packet collision will not occur. In view of the challenge, this paper proposes a novel and practical incremental relaying scheme that deals with the imperfect feedback. The key idea is to have pessimistic source and optimistic relay. The proposed scheme is simple and easily implementable. Simulation results show that the proposed scheme can outperform amplify-and-forward (AF), as well as approaching the performance of an idealized incremental AF with perfect feedback information.

Abstract The inherent temporal connectivity and existence of impairments in wireless channels pose challenges to network performance. Cooperative communication has been proposed as an effective technique to mitigate the imperfections of the wireless medium by exploiting channel diversity and availability of neighboring nodes that can act as relays. Although numerous cooperative communication techniques have been proposed in the literature, most of them do not consider Quality of Service (QoS) issues in a wireless sensor network. In this work, we study how cooperative communication can be applied to achieve differentiated QoS in a sensor network that uses Ultra‐Wideband (UWB) as its underlying PHY layer technology. SAUCeR is a slotted‐aloha based ultra‐wideband medium access control protocol with cooperative retransmissions that provides differentiated QoS in networks with varying traffic classes. Despite the high transmission rates provided by UWB, its impulse‐based nature renders many conventional carrier sensing MAC protocols incompatible. Consequently, SAUCeR utilizes slotted‐aloha to reduce packet collisions without the need for carrier sensing. Differentiated QoS is provided by allocating different resources (time slots) to varying traffic classes to segregate the contention between them. A QoS‐aware cooperative retransmission technique and two distributed relay selection schemes are also introduced to improve overall traffic throughput and reduce end‐to‐end delay, while preventing the starvation of any traffic class. Copyright © 2010 John Wiley & Sons, Ltd.

Upon the occurrence of a phenomenon of interest in a wireless sensor network, multiple sensors may be activated, leading to data implosion and redundancy. Data aggregation and/or fusion techniques exploit spatio-temporal correlation among sensory data to reduce traffic load and mitigate congestion. However, this is often at the expense of loss in Information Quality (IQ) of data that is collected at the fusion center. In this work, we address the problem of finding the least-cost routing tree that satisfies a given IQ constraint. We note that the optimal least-cost routing solution is a variation of the classical NP-hard Steiner tree problem in graphs, which incurs high overheads as it requires knowledge of the entire network topology and individual IQ contributions of each activated sensor node. We tackle these issues by proposing: (i) a topology-aware histogram-based aggregation structure that encapsulates the cost of including the IQ contribution of each activated node in a compact and efficient way; and (ii) a greedy heuristic to approximate and prune a least-cost aggregation routing path. We show that the performance of our IQ-aware routing protocol is: (i) bounded by a distance-based aggregation tree that collects data from all the activated nodes; and (ii) comparable to another IQ-aware routing protocol that uses an exhaustive brute-force search to approximate and prune the least-cost aggregation tree.

We are motivated to exploit the broadcast nature of a radio medium in combating its unreliable and time-varying characteristics. This leads to cooperative transmission where a neighbor node keeps a copy of an overheard packet and helps in retransmitting the overheard packet to its intended destination when the original transmission fails. Cooperative transmission improve wireless network performance through diversity gain, and can be performed in the forms of amplify-and-forward. Existing amplify-and-forward schemes either: (a) use multiple relays but in a non-incremental way, or (b) use only a single relay in an incremental way. Non-incremental (simple) schemes do not provide a good spectral efficiency. Also, using multiple relays can further improve diversity. This paper aims at proposing an incremental amplify-and-forward scheme that uses n relays, where n >; 1. In the proposed scheme, a relay will retransmit an overheard packet in a time slot, only if all the previous transmissions are not successful. The transmission cycle of a packet ends as soon as a packet has been received successfully by the intended destination or all the n relays has retransmitted their overheard packets. Analytical and numerical results show that the proposed scheme outperforms both the simple amplify-and-forward scheme and the single-relay incremental scheme in terms of a lower outage probability for a given spectral efficiency.

Wireless link is not reliable and has a time-varying quality. When a link quality is bad, all transmissions over the link are not successful and persistent retransmissions of the failed packet over the same link are not productive. Consider the broadcast nature of radio communications, a packet that fails to reach its intended receiver may be successfully received by neighbors. The idea of cooperative retransmission suggests that a neighbor should help in retransmitting an overheard packet to its intended receiver, instead of letting the original sender to persistently retransmit the failed packet. This paper proposes a simple MAC layer cooperation retransmission scheme, called CoRex. The proposed scheme deals with the three critical issues, namely relay selection, packet selection and fairness, all together. The performance of CoRex has been analyzed theoretically and evaluated through random event simulations. The results show that CoRex always outperforms the non-cooperative scheme in terms of throughput without compromising fairness.

CSMA/CA wireless MAC protocol is adopted in many standards. However, its performance at high contention level is less than desirable due to prolonged backoff period and collisions. We propose a novel cooperative MAC based on the Interweave Cognitive framework to combat high contention. In our setup, we incorporate a subset of self-organizing advanced nodes that opportunistically switch to a contention-free MAC protocol to ease network congestion in a cognitive and cooperative manner. Consequently, the whole network benefits from a higher and more stable throughput even at high contention level. Our theoretical and simulation results demonstrate that IC-MAC is effective in reducing the number of backlogged nodes and improving the throughput of up to 20% relative to CSMA/CA MAC.

This paper considers a wireless sensor network with Time-Hopping-Impulse-Radio Ultra Wide Band as the physical layer. The network is structured as a group of interconnected cells that are not synchronized with each other. In such an unsynchronized environment, inter-cell interference is not Gaussian, but generalized Gaussian. For such a non-Gaussian random interference, its impulsiveness is determined by the Kurtosis of the distribution. This paper shows that the Kurtosis can be controlled by adjusting some practical parameters, such as pulse shape, pulse length, slot duration, number of slots per frame, number of users, etc. Further, this paper shows that network throughput can be maximized by controlling the impulsiveness. The finding has been validated through simulations.

There is a lack of high-speed and low-cost wireless network at sea to meet the increasing need of maritime users. With this observation, we have envisaged a WiMAX mesh network for high-speed ship-to-ship/shore communications. Analysis of interference range in such maritime WiMAX mesh networks is presented in this paper. And based on the findings, scheduling transmission of MAC control messages and data packets within three-hop neighborhood is investigated for the purpose of minimizing interference. A model is developed for analysis of the interference range in maritime environment. With parameter values that are derived from measurements at sea, we show that by scheduling among three-hop neighborhood the probability a transmission being interfered by a concurrent transmission drops about 30%. Simulation results show that, with the simulation settings in this paper, by scheduling among three-hop neighborhood, the initial packet delay and the average packet delay can be reduced by about 17% and 15.6% in sea state 3.0, respectively. In sea state 6.0, the performance improvement in initial packet delay and average packet delay are about 45% and 19.3%, respectively.

Cooperation between wireless nodes to retransmit data for the other users introduces multiuser diversity to a wireless network and increases the system throughput. In this paper, the optimal cooperative relaying strategies in the MAC layer are analyzed while considering the UWB unique properties such as fine ranging and immunity to small scale fading. Specifically, the optimal cooperation strategies in the absence of coordination message passing between relays are determined in order to maximize the system throughput while reducing the control packet overhead. Mobile networks are also considered, in which the relays should exchange their ranging information together in some update intervals. The optimal update interval length is calculated in order to maximize the system throughput. More importantly, we show that if this optimal update interval is used, the optimal cooperation strategies in the mobile case will be similar to those in the static network. Two different relay selection schemes, namely proactive and reactive settings, are considered. Analysis and simulations confirm that the proposed UWB-based Cooperative Relaying Scheme, UCoRS, can achieve a considerable diversity gain in spite of its implementation simplicity. UCoRS also minimizes the number of control packets that are required for the optimal cooperation, which leads to the energy efficiency in the UWB costly data-receiving process.

There is a lack of broadband wireless network in sea to meet the increasing needs of modern maritime users and we have envisaged WiMAX mesh networks for high-speed and low-cost ship-to-ship/shore communications. In such a maritime WiMAX mesh network, due to the long transmission distance and the distributed scheduling among two-hop neighbors, a single frequency channel may not be sufficient to provide the required bandwidth. An effective solution is to employ multiple frequency channels, by which the network capacity can be greatly increased. This paper presents operation of multi-channel transmission in maritime WiMAX mesh networks including allocation of minislots and frequency channels. The operation is based on a distributed adaptive time slots allocation and use of availability tables tracing minislots status. In the design, routing information is delivered in control subframe portion, and then the spreading of routing information can be speed up and less overhead in control slots can be used to describe and broadcast the availabilities of the minislots. Simulation results show that with the proposed scheme, by multi-channel transmission, the network performance can be improved in average packet delay and packets delivery ratio.

It is well-known that throughput of wired multi-hop, multi-commodity networks can be maximized by employing back-pressure scheduling. With this approach, packets belonging to different destinations are dynamically routed/scheduled in a network based on buffer occupancies and link quality. There has been a considerable amount of research on applying back-pressure scheduling in the wireless environment; usually by abstracting each wireless channel as a point-to-point link and therefore, ignoring the fundamental wireless broadcast property. In this paper, we consider a two-hop wireless cooperative network and characterize the minimum throughput gain obtained by exploiting broadcast property in back-pressure scheduling. Numerical results are provided to support our analysis.

In cooperative retransmissions, nodes with better channel qualities help other nodes in retransmitting a failed packet to its intended destination. In this paper, we propose a cooperative retransmission scheme where each node makes local decision to cooperate or not to cooperate at what transmission power using a Markov decision process with reinforcement learning. With the reinforcement learning, the proposed scheme avoids solving an Markov decision process with a large number of states. Through simulations, we show that the proposed scheme is robust to collisions, is scalable with regard to the network size, and can provide significant cooperative diversity.

In cooperative wireless networks, the source node transmits the packets to its destination with the help from the cooperative nodes. However, existing routing metrics in the literature do not take into account the cooperative gain in choosing the next hop in a multi-hop network. In this paper, we propose a new routing metric that accounts for the potential cooperative gain a candidate next hop may receive from its neighbors. As such, a more efficient route selection can be done for better end-to-end performance. We call the proposed routing metric, Expected Transmission Time with Cooperation, and show that it outperforms hop count as a routing metric in terms of end-to-end transmission time (packet delay).

We envisage extending the coverage of existing terrestrial wireless broadband wireless networks to the sea so that cost-efficient wireless access is available to the ships near the shore. The coverage extension is achieved through a multi-hop WiMAX wireless mesh networks where ships, maritime beacons and buoys are the nodes. In such a multi-hop network, routing protocol plays an important role in ensuring reliable end-to-end packet delivery. Compared to AOMDV and OLSR, AODV has been found as a more suitable routing protocol in terms of average packet delay, packet delivery ratio, and implementation complexity. AODV requires route request messages being broadcast during route discovery process. However, WiMAX mesh MAC protocol is not efficient in supporting broadcast of data packets that carry the route request. This inefficiency is due to need of performing the three-way-handshaking process in reserving a data slot before transmitting each route request. As a result, AODV suffers from large initial packet delay and average packet delay. In view of the problem, this paper proposes a method to efficiently deliver the AODV routing messages by piggybacking them on the existing WiMAX mesh MAC control messages. As such, the three-way-handshaking is avoided leading to a faster transmission of routing messages. Simulation results confirm that the proposed scheme can lead to an improvement in initial packet delay, weighted average delay, and packet delivery ratio.

We envisage extending radio coverage of the existing terrestrial wireless broadband networks to the sea to provide ships with high speed connection to the Internet. This is achieved by forming a WiMAX-based maritime wireless mesh network where ships are network nodes connected to the land station across multiple hops. In such a wireless mesh network, routing protocol plays an important role in providing efficient and reliable communications. This paper proposes a routing protocol, called MRPT (MAC-based Routing Protocol for TRITON), that piggybacks routing information on WiMAX mesh MAC control messages. This provides proactiveness and readily available multi-path for traffic from ship to land station. For traffic from land station to ship, the proposed routing protocol uses a bitmap encoding to efficiently inform land station of the constructed routing tree. Simulation results confirm that MRPT outperforms AODV, AOMDV and OLSR in terms of delay and throughput.

We envisage extending radio coverage of the existing terrestrial wireless broadband networks to the sea to provide ships with cost-efficient high-speed connection to the Internet. This is achieved by forming a WiMAX based maritime wireless mesh network where ships are network nodes connected to the land station across multiple hops. In such a maritime wireless mesh network, time slot allocation is an important issue as it affects the performance in terms of throughout and delay. This papers proposes a distributed adaptive time slot allocation (DATSA) scheme for WiMAX mesh MAC protocol. DATSA is a distributed scheme that allocates time slots robustly by taking into consideration difference between radio reception range and interference range, and latency in scheduling control messages. DATSA has a method to monitor reception quality of an allocated time slot, in order to detect the effect of topology changes due to ship mobility, etc. Based on the monitoring outcome, the method adaptively changes the time slot allocation if necessary. We have evaluated DATSA through random event simulation using QualNet. The simulation results confirm that DATSA outperforms the original WiMAX mesh MAC protocol that has no adaptive time slot allocation, in terms of throughput, average packet delay, and packet delivery ratio.

The challenging problem of cooperative retransmission in the wireless networks is investigated in this paper. This paper introduces the centralized and distributed Markov decision process (MDP) frameworks in the context of cooperative retransmission. Specifically, a MDP model with the global channel information is first constructed for the cooperation problem in the MAC layer. It is shown that this global MDP is able to perform optimally, where the objective is to minimize the total number of required transmissions for a successful packet delivery to the destination. When the global information is unavailable, we show that the suitable distributed MDP models can replace the global model for a near-optimal performance. Furthermore, the reinforcement learning methods are investigated when the MDP model is unavailable. Interestingly, simulation results confirm that the learning methods also provide an acceptable performance despite their simplicity and low overhead.

A transmitted packet that fails to reach its intended destination may be correctly received by neighbor nodes due to the broadcast nature of the wireless medium. In a cooperative retransmission scheme, these neighbor nodes, known as relays, can retransmit the failed packet on behalf of the original source node. The challenge is that multiple concurrent transmissions may lead to collision at the destination, and thus the problem is to decide which relay should help in retransmitting the failed packet so that the destination can successfully receive it. This paper proposes a decentralized partially observable Markov decision process (DEC-POMDP) model for selecting the relays to perform the cooperative retransmission. The proposed DEC- POMDP model does not require global channel state information (CSI). In addition, it is robust to noise in CSI measurements. Furthermore, the proposed DEC-POMDP scheme utilizes the gradient descent learning method to eliminate the need for a wireless channel model. We show that the proposed learning method based on the DEC-POMDP model can perform near optimally in the absence of a channel model and despite its implementation simplicity.

Ultra-wideband (UWB) is a physical (PHY) layer technology that promises high transmission rates, as well as high resistance to noise and multipath effects. However, the impulse-based nature of UWB, coupled with its low transmission power, makes it difficult to enable efficient detection of the signals. Consequently, conventional carrier-sensing based MAC protocols cannot be used with a UWB PHY. In this paper, we propose SASW-CR - a Slotted Aloha MAC protocol for UWB networks with Sliding contention Window and Coperative Retransmissions, which provides QoS support without the use of carrier sensing. SASW-CR utilizes the slotted-Aloha technique to avoid carrier sensing and reduce packet collisions. In addition, it makes use of differentiated contention windows to provide varying classes of QoS for different traffic classes. A cooperative retransmission technique is also introduced to improve the overall traffic throughput and reduce end-to-end delay. The efficacy of our protocol is demonstrated through simulations.

This paper details a novel approach of developing a low-cost and high speed maritime ship-to-ship/shore mesh network to complement or replace satellite communications in narrow water channels or traffic lanes close to shorelines. To design the system, we gathered requirements from typical users of the system. We then carried out preliminary studies such as radio channel propagation over sea water, ship movement patterns, ship rocking and its effect on radio transmission and network connectivity to determine the feasibility of using a mesh network for maritime networks. We present the architecture and detail some of our routing and scheduling design considerations that address the unique challenges of the maritime environment and provide us with framework for providing fair and equal opportunity access to users.

The inherent near-far effect in wireless networks causes nodes that are further away from the receiver to suffer from throughput degradation, as packets from nodes that are nearer are typically received with greater signal strengths. This unfair situation is traditionally overcome by power control. However, when power control is not feasible, for example in tiny sensor nodes with power-limited batteries, alternative solutions have to be utilized to achieve fairness in the network. In this paper, we propose U-LiBRA - an UWB Location Based Resource Allocation scheme to alleviate the contention between near and far nodes in a TH-UWB sensor network. U-LiBRA allocates different time slots to nodes that are at varying distances from the receiver, so that nodes that are further away from the receiver can achieve higher throughput than what they would typically obtain under the influence of the near-far effect. Simulation results show that U-LiBRA can effectively mitigate the near-far effect and improve fairness in the absence of power control.

For a given multi-hop route in an IEEE 802.16 mesh network, we are interested in finding its end-to-end capacity so that admission control can be performed. The end-to-end capacity is difficult to determine due to the interference between communicating nodes caused by the broadcast nature of radio propagation. In this paper, we first propose a method to determine link capacity between two nodes, after which a zone-based method is used to obtain the end-to-end capacity of a route. We demonstrate the effectiveness of the link capacity and end-to-end capacity computing methods through simulations.

We envisage coverage extension of the high bit rate terrestrial communication networks to the ships to reduce the cost in maritime communications. The coverage extension is achieved by forming a mobile wireless mesh network amongst neighboring ships, marine beacons and buoys. The wireless mesh network will be connected to the terrestrial networks across multiple hops via land stations at shore. In such a multi-hop wireless network, routing protocol is important. This paper compares the performance of three existing routing protocols in a maritime communication environment. The three routing protocols are OLSR, AODV and AOMDV. The performance comparison is done via simulation. In the simulation, the wireless mesh network is formed using WiMAX mesh MAC protocol. Also, the random sea surface movement and maritime communication link characteristic are simulated. From the simulation results, we found that OLSR is not as efficient as AODV and AOMDV. Also, compared to AODV, the performance of AOMDV is less affected by sea condition.

In this work, we study the time-slot allocation problem in a multi-sink single-hop TH-UWB network scenario, where the traffic from a sensor node is anycasted via a single hop to any one of multiple sinks. The slot allocation problem is formulated as an optimization problem and shown to be NP-hard. We then present a heuristic to increase network throughput and fairness as compared to a random allocation. In the proposed heuristic, nodes that are of similar distances to any sinks are grouped together to utilize the same set of TH slots for transmissions. Simulations show that the proposed heuristic improves both throughput and fairness, scales with multiple sinks and can be used as a simple admission control mechanism.

As a prevalent reliable transport protocol in the Internet, TCP uses two key functions: the additive-increase multiplicative-decrease (AIMD) congestion control and a cumulative ACK technique for guaranteeing delivery. However, these two functions lead to the inefficiency of TCP in ad hoc networks where the TCP connections have very small bandwidth-delay products (BDPs) and there are frequent packet losses in the network due to various reasons such as route breakages and radio interference. In this paper, we show that if the BDP of a path is as low as several packets and is known before the connection establishment, any AIMD-style congestion control is costly and is hence not necessary for ad hoc networks. On the contrary, a technique for guaranteeing reliable transmission and recovering packet losses plays a more critical role in the design of a transport protocol over ad hoc networks. With this basis, we propose a novel effective datagram-oriented end-to-end reliable transport protocol for ad hoc networks, which we call Datagram Transport Protocol for Ad hoc networks (DTPA). The proposed scheme incorporates two techniques: a fixed-size- window-based flow-control algorithm and a cumulative bit-vector-based selective ACK strategy. We then develop a mathematical model for evaluating the performance of DTPA based on these two techniques. An optimum transmission window is determined for an n-hop chain and is computed to be the BDP of the path plus 3. The protocol is verified using GloMoSim, and simulation results show that our proposal substantially improves the network performance in terms of throughput, round-trip time, number of retransmissions, and IP queue size.

Bandwidth delay product (BDP) represents the maximum amount of allowed unacknowledged data in flight at any moment in the network. Due to the spatial reuse property of 802.11 MAC protocol in multi-hop ad hoc networks, the BDP of the path approximates 1/4 of the path length and is a value of several packets. With such a small BDP, TCP cannot work efficiently since its congestion window increases far beyond BDP most of the time, which can generate heavy congestion in the network. This paper presents a mathematical approach to derive an optimum maximum congestion window for TCP Reno over 802.11 based ad hoc networks. We adopt a Markov renewal approach to analyze the behavior of TCP Reno, which incorporates an accurate and realistic modelling of the fast-recovery process. Through analysis, we find that the optimum maximum congestion window is 6 packets for a multi-hop chain with any path length.

A cross layer approach is important for designing multi-hop wireless network routing protocols. In this paper, we maximize the path reliability by proper scheduling of transmissions at link layer over different paths. In our scheme, each node involved in the routing maintains two paths towards the destination. When forwarding a packet, the transmissions at link layer are optimally scheduled by considering the instantaneous channel reliability, the end-to-end reliability at the parent nodes and the remaining number of transmissions at this hop. We convert the decision process of the transmission scheduling into a Markov decision model and derive the optimal policy using backward induction algorithm. Results show that the end-to-end reliability can be improved significantly with the optimal transmission schedule.

We propose a packet-level model to investigate the impact of channel error on the transmission control protocol (TCP) performance over IEEE-802.11-based multihop wireless networks. A Markov renewal approach is used to analyze the behavior of TCP Reno and TCP Impatient NewReno. Compared to previous work, our main contributions are listed as follows: 1) modeling multiple lossy links, 2) investigating the interactions among TCP, Internet Protocol (IP), and media access control (MAC) protocol layers, specifically the impact of 802.11 MAC protocol and dynamic source routing (DSR) protocol on TCP throughput performance, 3) considering the spatial reuse property of the wireless channel, the model takes into account the different proportions between the interference range and transmission range, and 4) adopting more accurate and realistic analysis to the fast recovery process and showing the dependency of throughput and the risk of experiencing successive fast retransmits and timeouts on the packet error probability. The analytical results are validated against simulation results by using GloMoSim. The results show that the impact of the channel error is reduced significantly due to the packet retransmissions on a per-hop basis and a small bandwidth delay product of ad hoc networks. The TCP throughput always deteriorates less than ~ 10 percent, with a packet error rate ranging from 0 to 0.1. Our model also provides a theoretical basis for designing an optimum long retry limit for IEEE 802.11 in ad hoc networks.

In a 802.11 based mobile ad hoc network (MANET), the routing protocol may wrongly assume that a route is broken due to temporal packet loss in connectivity arising from multiple packet collisions, which we term as a false route breakage. In this paper, we investigate the impact of false route breakages in MANETs. It is found that false route breakage is dependent on the size of packets transmitted in a network and the path length of a source-destination pair. We present a protocol enhancement to the IEEE 802.11 MAC protocol which increases the reliability of wireless links by reducing false route breakages. We achieve the goal of alleviating false route breakages by initiating a HELLO message to the sender whenever the number of RTS received by a receiver exceeds a threshold. The simulation results show that the proposed modification substantially reduces the false route breakages and improves throughput by up to 35%

How the QoS performance of a communication network is affected by the disturbances, such as channel impairments link failures, node mobility, etc.? In other words, how robust is the QoS performance? Before answering these questions, we need a clear definition of QoS performance robustness and a method to quantify it. This paper contributes in the two aspects. It first proposes a new approach to define performance robustness before outlining a method to quantify and calculate robustness as a metric. Later, a case study is presented where the proposed robustness metric is used to compare two existing routing algorithms for a wireless multi-hop network

This paper analyzes the TCP performance in an 802.11 based multi-hop ad hoc network. The analysis is unique because it tries to quantify the throughput of a TCP flow after considering the interaction between TCP's congestion window size and 802.11's MAC (medium access control) contention window size. The analysis results in formulae to compute the throughput of a single TCP flow for an n-hop string topology under the ideal situation where there is no packet loss in the network. The analytical results have been validated by benchmarking against simulation results from ns-2. The outcome of the analysis is useful when ad hoc networks are adopted as an extension to the Internet because TCP is the prevalent transport protocol for reliable data transmissions in the Internet.

Although several routing algorithms for LEO satellite networks have been proposed in the literature, the issue of providing guaranteed end-to-end delay bound QoS for with good throughput has not been solved. The motivation to design such an algorithm is based on the fact that LEO satellite networks are likely to play an important role in the future Internet. In this paper, weighted fair queuing (WFQ) is introduced into the LEO satellite system with the aim of providing end-to-end delay guarantees. High performance satellite routing (HPSR), which is able to provide a guaranteed end-to-end delay bound for LEO satellite networks with high throughput, is put forward. Unlike previously reported algorithms, HPSR applies a route computation algorithm which takes statistical multiplexing among connections into consideration, and which is able to obtain good system throughput. Through simulations on an Iridium-like constellation, the proposed approach is shown to achieve a guaranteed end-to-end delay bound with higher throughput as compared to a previously reported routing scheme.

In this paper, we develop analytical models for a single persistent TCP flow in the presence of channel error-induced packet loss over IEEE 802.11 based multi-hop networks. Two analytical models are proposed, based on different packet loss models: periodic packet loss model and i.i.d. random packet loss model. For the latter, we develop a stochastic model using the Markov renewal reward approach. The analytical results are validated against results using the ns simulator. The results show that the impact of the channel errors is reduced significantly with packet retransmissions on a per-hop basis and the two models are valid for a packet error rate ranging from 0 to /spl sim/0.05.

Multicode-code division multiple access (CDMA) supports a variety of transmission rates within a wireless network. However, providing packet-delay guarantees in a multicode-CDMA network is difficult because its transmission capacity is time varying even in an error-free wireless channel. In this paper, we develop a packet-scheduling algorithm called multicode-deficit round robin (DRR) as a solution to the problem. The basic idea of multicode-DRR is to separate the time-varying capacity into a deterministic component and a variable component, and to use these components to serve time-sensitive and non-time-sensitive traffic, respectively. With the proposed scheduling algorithm, simulation results have confirmed that the maximum packet delays for time-sensitive traffic never exceed their target upper bounds.

Wireless bandwidth is a very precious resource and must be used efficiently. The efficiency is normally measured in terms of utilization or throughput. However, a high throughput alone is no longer sufficient when there is time-sensitive traffic to support in a wireless network because this traffic has delay requirement. Time-sensitive packets must be delivered before a certain delay upper bound or risk being dropped. Thus, packet drop ratio should be used to measure the ability in meeting the delay requirement. This paper proposes a novel resource allocation scheme called ERATS that capitalizes on the time-varying nature of a wireless channel to achieve a higher throughput at the same time of providing an accurate proportionally differentiated packet drop ratio. Simulation results using OPNET have indicated the efficiency of ERATS.

A MultiCode-CDMA network that is capable of providing quality-of-service guarantees will find widespread application in future wireless multimedia networks. However, providing delay guarantees to time-sensitive traffic in such a network is challenging because its transmission capacity is variable even in the absence of any channel impairment. We propose and evaluate the performance of a novel transmission scheduling scheme that is capable of providing such a delay guarantee in a MultiCode-CDMA network. The proposed scheme drops packets to ensure that delays for all transmitted packets are within the guaranteed target bounds, but packets are dropped in a controlled manner such that the average dropping ratios of a set of time-sensitive flows can be proportionally differentiated according to the assigned weighting factors or shares. We provide extensive simulation results to show the effectiveness of the proposed scheme as well as to study the effects of various parameters on its performance. In particular, we show that it can simultaneously guarantee a delay upper bound and a proportionally differentiated dropping ratio in a fading wireless channel for different traffic loads, peak transmission rates, and weighting factors of individual flows.

We introduce the concept of generalized stochastically bounded burstiness (gSBB) for Internet traffic, the tail distribution of whose burstiness can be bounded by a decreasing function in a function class with few restrictions. This new concept extends the concept of stochastically bounded burstiness (SBB) introduced by previous researchers to a much larger extent - while the SBB model can apply to Gaussian self-similar input processes, such as fractional Brownian motion, gSBB traffic contains non-Gaussian self-similar input processes, such as /spl alpha/-stable self-similar processes, which are not SBB in general. We develop a network calculus for gSBB traffic. We characterize gSBB traffic by the distribution of its queue size. We explore the property of sums of gSBB traffic and the relation of input and output processes. We apply this calculus to a work-conserving system shared by a number of gSBB sources, to analyze the behavior of output traffic for each source and to estimate the probabilistic bounds for delays. We expect this new calculus to be of particular interest in the implementation of services with statistical qualitative guarantees.

Existing multicode-CDMA MAC protocols do only single dimensional access control either in the code or time domain, and thus result in a complex optimisation problem. In this paper, we propose a MAC protocol which can do simultaneous code-time access control to avoid the optimisation problem, and to achieve better system utilisation. In order to do that, the proposed protocol decouples the function of transmission ordering from the function of packing all the scheduled transmissions in the resource space. As such, different transmission scheduling algorithms can be adopted without altering the protocol. A water filling approach is used for efficient transmission packing where each of the scheduled transmissions is treated as a rectangular capsule with an arbitrary size and the resource space is viewed as a water container. Simulation results indicate that the proposed protocol can achieve higher throughput compared to single dimensional access control protocols. Therefore, the proposed MAC protocol is a more efficient one.

Multicode-CDMA is a good choice for wireless networking because it can support devices with different peak transmission rates within one network and hence, enables cost scalability. However, delivering delay guarantee in a multicode-CDMA network is difficult because its capacity is variable even in a perfect wireless channel. We develop a scheme called multicode-DRR as a solution to the problem. The basic idea of multicode-DRR is to separate the variable capacity into a deterministic component and a variable component, and to use these components to serve time-sensitive traffic and non-time-sensitive traffic, respectively. Simulation results confirm that the maximum time-sensitive packet delay never exceeds the theoretical upper bound when the devices are served using the proposed scheme. In short, multicode-DRR is significant because it enables a multicode-CDMA network to deliver deterministic upper delay guarantee.

Future wireless networks need to support different service requirements. Ho-sever, the exiting methods of specifying QoS commitments, namely qualitative commitment and quantitativ e commitment are not perfect for a wireless communication environment. In this paper, we propose a new concept called compound QoS commitment which combines qualitative and quantitative commitments within a single service commitment. As such, the proposed concept can provide a practical approach to deal with the highly variable wireless netw ork capacijr. Since each compound QoS commitment has tw o degrees of freedom, it m\ also increase the fiexibilit y in committing an ahievable QoS. In order to show the feasibility of the proposed concept, we present a scheduling algorithm whic hcan sim ultaneouslypro vide a proportional dropping ratio guarantee and a deterministic upper delay guarantee to a flow. Numerical results confirm that the algorithm is capable of delivering the tw o guarantees simultaneously.