To address the explosive growth of number of mobile users in future generations of wireless networks, Non-Orthogonal Multiple Access (NOMA) has received significant attention. In this work, we propose an incentive driven content shifting framework to reward users which push multimedia data content from an Orthogonal Multiple Access (OMA) link to a NOMA link. The objective of the framework is to benefit both the user and the base station by simultaneously improving the user’s Quality of Experience (QoE) and the base station’s profits. The key issue of strategically splitting the data among the available NOMA and OMA links are studied to attain the best possible service. According to our study, OMA could be leveraged for transmission of important frames while NOMA is suitable for frames with lesser importance. Using game theoretic methods, we develop a method to attain the Nash Equilibrium of the solution. Simulation studies showcase the merits and potentials of the proposed incentive mechanism to encourage users transmitting certain data through NOMA links.

Non-Orthogonal Multiple Access (NOMA) is one of the promising solutions for next-generation wireless multimedia services to mitigate traffic congestion and reduce latency. Orthogonal Multiple Access (OMA) on the other hand has been used over the years to transmit content wirelessly. The merits offered by OMA would make it co-exist along with NOMA in the upcoming years. The key idea of this paper is to leverage Uber/Lyft ride-share philosophy to design the wireless access pricing model to be "orthogonality-centric"; being aware of the shared NOMA and exclusive OMA access price differences in wireless networks. The efficacy of the developed pricing model is then studied on a hybrid network which supports both NOMA and OMA resource blocks. The utility definitions for both the base station and the mobile user are mathematically modeled and the profit maximization interplay between the two parties is analyzed using game theoretic methods. An algorithm to derive Nash Equilibrium solution is presented. The simulations showcase the efficacy of the developed orthogonality driven pricing framework developed in this paper. Furthermore, the results indicate that the non-uniform orthogonality-centric pricing yields better utilities for both the base station and the end user.

Wireless multimedia communications is one of the most rapidly growing technologies of the decade. With explosive growth in network traffic, the service providers struggle to provide satisfactory Quality of Experience (QoE) to the users and increase revenue. Non-Orthogonal Multiple Access (NOMA) has been proposed to cater multiple users simultaneously in each resource block by exponentially increasing the network capacity. However, the strategic allocation and trading of NOMA resource blocks are still open issues. In this work, we treat a NOMA resource block as a commodity representing its channel quality and the importance of data it carries. We then chalkup the innovative and appealing QoE-price interplay to promote NOMA resource block trading as a suitable candidate for future-generation wireless mobile networks. The proposed framework benefits both the utilities of users and service providers. The proposed approach is solved by deriving the Nash Equilibrium of the network interactions using a best-response game. Simulations suggests further exploration of the potentials to the adaptation of proposed framework for NOMA wireless multimedia communications.

Non-Orthogonal Multiple Access (NOMA) is one of the promising solutions for next-generation wireless services to mitigate traffic congestion and reduce latency. However, the issues such as regulating network revenue and ameliorating end-user Quality of Experience (QoE) are still open challenges. In this work, we propose the concept of Non-Orthogonal Multiple Access Pricing (NOMAP), to bridge the gap between price and QoE in NOMA resource allocation. The framework was then applied to a NOMA network scenario, and the problems of power allocation and resource block selection were investigated. The main contribution of this paper is to show that higher utilities can be achieved by dynamically pricing the NOMA resource blocks and by allowing the users to have a choice in resource management. In addition, an algorithm to achieve optimality in terms of Nash equilibrium is provided as an implementation example. The simulations carried out using MATLAB showcase the efficacy of the developed NOMAP framework. Furthermore, the results indicate that the proposed pricing significantly outperforms the traditional uniform pricing schemes.

Improving Quality of Experience (QoE) of User Equipment (UE) in wireless multimedia services is a critical challenge. In this paper we study the joint design of high level dynamic video Quantization Parameter (QP) and the low level power control in QoE-driven downlink wireless multimedia services. Furthermore, we study QoE performance with new Non-Orthogonal Multiple Access (NOMA) schemes in the Base Station (BS) - UE multimedia downlink, and discuss the performance in comparison with conventional Orthogonal Multiple Access (OMA). We mathematically model UE's QoE gain (also known as utility) by considering UE's perceived data quality and the corresponding data cost. Then we show that there exists an optimal data consumption option for UE to achieve utility maximization based on different cost coefficients. In addition, the power allocation strategies and their associated constraints are investigated in both OMA and NOMA transmission schemes. Finally, through numerical simulations, we quantitatively analyze the impact of low level power allocation and high level QP control on UEs' utility gain and the system throughput performance.

In Non-Orthogonal Multiple Access (NOMA) downlink the Base Station (BS) transmits to multiple User Equipments (UEs) at the same time and the same frequency with different power levels. However making full use of the promising NOMA technology to relay multimedia contents for UEs in wireless media service is an open issue. In this paper, a Quality of Experience (QoE)-centric multimedia relaying scheme is proposed, where the NOMA is not only applied at the downlinks between the BS and UEs, but also at the Device-to-Device (D2D) relay links among UEs during the relaying phase. By mathematically analyzing the Signal to Interference plus Noise Ratio (SINR) model in downlinks and D2D relay links, we show that the new QoE-centric relay scheme would significantly improve the multimedia QoE of UEs, especially for the UEs with low SINR. In addition, the QoE and energy consumption models are developed in order to comprehensively analyze the system performance. Finally, through numerical simulation we quantitatively analyze the energy efficiency and QoE performance of UEs in different NOMA systems with various numbers of UEs.

One of the promising features of 5G networks is device‐to‐device (D2D) communication that enables direct transmission between D2D user equipments (UEs). Besides the traditional cellular transmission mode, UEs can select between the reuse and dedicated modes. In this study the authors consider a scenario where a communicating D2D pair and a cellular UE that communicates with an evolved Node‐B can use the same spectrum. It is assumed that the cellular UE can move in the network while the D2D UEs are static. The movement of the cellular UE can affect the quality of the communication between the D2D pair. Therefore, the transmission mode between the D2D UEs might change to keep the best quality. In this study the authors propose a new mobility management and vertical handover algorithm that handles the transmission mode transition during the D2D connection to maximise the overall throughput. The algorithm uses distance from the border and critical direction set as mobility variables that are analytically determined. These variables are calculated using a mode selection map that is derived analytically when pathloss and fading models are used. Finally, in order to analyse the performance of the proposed handover algorithm, the authors analytically calculate handover rate and sojourn time metrics.

This article looks at some of the challenges related to the deployment of the Internet Of Things (IoT), specifically to ascertain that security becomes an integral part of the technology rather than a bolted-on wrapper of limited efficacy. IoT security (IoTSec) is needed at all `layers' of the IoT environment and may be specific to the IoT `layer' in question.

The Internet of Things (IoT) is entering the daily operation of many industries; applications include but are not limited to smart cities, smart grids, smart homes, physical security, e-health, asset management, and logistics. For example, the concept of smart cities is emerging in multiple continents, where enhanced street lighting controls, infrastructure monitoring, public safety and surveillance, physical security, gunshot detection, meter reading, and transportation analysis and optimization systems are being deployed on a city-wide scale. A related and cost-effective user-level IoT application is the support of IoT-enabled smart buildings. Commercial space has substantial requirements in terms of comfort, usability, security, and energy management. IoT-based systems can support these requirements in an organic manner. In particular, power over Ethernet, as part of an IoT-based solution, offers disruptive opportunities in revolutionizing the in-building connectivity of a large swath of devices. However, a number of deployment-limiting issues currently impact the scope of IoT utilization, including lack of comprehensive end-to-end standards, fragmented cybersecurity solutions, and a relative dearth of fully-developed vertical applications. This paper reviews some of the technical opportunities offered and the technical challenges faced by the IoT in the smart building arena.

With the popularity of multimedia sensing at cloud edges and the reducing cost of the Internet of Things (IoT) fog devices and systems, new challenges have been posed to efficiently deal with the big data multimedia traffic generated from IoT sensing units. Specifically, in this paper we introduce the concept of multimedia sensing as a service (MSaaS), and propose a generalized premium prioritization-based quality of experience paradigm for wireless big-volumes-of-data (BVDs) multimedia communications, with significant energy saving potentials for future multimedia IoT devices and systems. The key contribution of this new framework is its data diversity flexibility at the application layer, which could be flexibly adopted by future multimedia communication systems. Data dependencies in spatial, frequency and temporal domains are analyzed, and interaction with uplink resource allocation optimization are investigated with regards to wireless communication energy cost estimation. Extensive simulation results demonstrate that the proposed prioritization-based communication paradigm has significant energy saving potentials for BVD MSaaS wireless multimedia communications at cloud edges and fogs.

Device-to-Device (D2D) transmission is a promising technology which enables the User Equipments (UE) in 5G cellular networks to directly communicate without going through the evolved Node-B (eNB). In such networks UEs should select a Transmission Mode (TM) amongst reuse, dedicated, and cellular modes by maximizing the overall transmission throughput or referring to a mode selection map. The selection map identifies the mode which results in the highest data rate given the current state of the network. This paper presents a new analytical framework for the derivation of the selection map of D2D enabled cellular networks. While this problem was treated in the literature through numerical simulations, our approach is analytical and consequently fast and precise.

Device-to-Device (D2D) communication is one of the new features introduced for Long Term Evolution-Advanced (LTE-A) and beyond networks. In this paper we address the problem of communication mode selection for a pair of User Equipments (UEs). In particular we assume that the paired UEs can choose from the reuse, dedicated, and cellular modes. While this problem was treated in the literature for Single-Input-Single-Output (SISO) case, we derive models for networks where UEs and evolved-Node-Bs (eNBs) exploit Multiple-Input-Multiple-Output (MIMO) techniques with four antennas at each side. This approach requires design of the pre-coding matrices at each node which poses a challenge in the reuse mode due to the non-convexity problem. To solve this issue we propose a distributed iterative algorithm. The numerical study compares the performance of the MIMO based approach with that of the SISO case, and the results show that the presented MIMO based mode selection method provides significantly higher network throughput than that of the SISO based mode selection method for the same D2D transmission range.

Device-to-Device (D2D) communication is envisioned as a promising technology to significantly improve the performance of current cellular infrastructures. Allocating resources to the D2D link, however, raises an enormous challenge to the co-existing D2D and cellular communications due to mutual interference. While there have been many resource allocation solutions proposed for D2D underlaying cellular network, they have primarily focused on the intracell scenario while leaving the intercell settings untouched. In this paper, we investigate the resource allocation problem for intercell D2D communications underlaying cellular networks, where D2D link is located in the overlapping area of two neighboring cells. We present three inter-cell D2D scenarios regarding the resource allocation problem. To address this problem, we develop a repeated game model under these scenarios. Distinct from existing works, we characterize the communication infrastructure, namely Base Stations (BSs), as players competing resource allocation quota for D2D demand, and define the utility of each player as the payoff from both cellular and D2D communications using radio resources. We also propose a resource allocation algorithm and protocol based on the equilibrium derivations. Numerical results indicate that the developed model not only significantly enhances the system performance including sum rate and sum rate gain, but also sheds lights on resource configurations for intercell D2D scenarios.

Extreme physical conditions in the deep space environment result in the severe challenge of unreliable deep-space data communications. Moreover, high data rate services such as Earth-Mar multimedia communication in space exploration applications consume significant amount of energy, while the limited battery energy storage forms another communication bottleneck. To overcome these challenges, we propose an algorithm to adaptively control transmission power in a two-hop relay Mars-Earth communication link, to improve end-to-end throughput performance while minimizing the energy consumption at different transmission stations. In the proposed approach, transmission power of each communication station is adaptively adjusted according the energy storage leftover at each node. To achieve such optimal power adaptation, energy budget constraint is considered in the overall optimization process. Simulation results demonstrate the proposed power control methodology can bring significant improvement of throughput performance to support traffic intensive multimedia applications by exploring the limited energy budget.

Using harvestable energy in Wireless Sensor Networks (WSNs) has gained considerable popularity recently. However, how to utilize the unstable power supply to achieve quality performance is still a challenge. In this paper, we propose a Weight-Optimized Source Rate Optimization (WOSRO) approach which allows the WSN system to adaptively control source coding rates by choosing the most valuable data packets to transmit. In this approach, the packet selection strategy is optimized by considering multimedia distortion reduction, energy cost, energy neutrality constraint and power saving efficiency. Simulation results show that the proposed data packet selecting strategy significantly improves data transmission quality by exploring harvesting-storage energy neutrality and multimedia data packet importance.

In this paper, a new cooperative spectrum sensing algorithm is proposed for a cognitive radio network with multiple secondary users (SUs) sharing spectrum with one or more primary users (PUs). Unlike most previous spectrum sensing algorithms that do not consider the time domain traffic statistics of the PU, the algorithm in this paper is developed by exploiting the statistical properties of the PU's transmission pattern, which is modeled with a Markov chain with two states: busy (1) and idle (0). Each SU performs energy detection based on an observation of the Markov chain, and the detection results are forwarded to a fusion center (FC) through a noisy channel. The FC recovers the decisions of the SUs by using a new progressive maximum a posteriori (MAP) algorithm, where the a priori probability essential to the MAP detection is obtained by progressively estimating the transition probabilities of the Markov chain. Analytical expressions are derived for the probabilities of false alarm and missing detection, with both the majority data fusion rule and the OR data fusion rule. Both theoretical analysis and simulation results indicate that the proposed algorithm can provide reliable and efficient spectrum sensing over a large range of system configurations.

Existing studies have demonstrated that uneven and dynamic usage patterns by the primary users of license-based wireless communication systems can often lead to temporal and spatial spectrum underutilization. This provides an opportunity for the secondary users (SUs) to tap into underutilized frequency bands provided that they are capable of cognitively accessing systems without colliding or impacting the performance of the primary users (PUs). When there are multiple networks with spare spectrum, secondary users can opportunistically choose the best network to access, subject to certain constraints. In cognitive radio systems, this is referred to as the network selection problem for secondary users. This paper develops a Markov queuing model to obtain the maximum allowable arrival rate of secondary users subject to a target collision probability for the primary users. Based on this model, we design a novel Collision-Constrained Network Selection (CCNS) method that maximizes secondary users' throughput subject to a given PU collision probability. Further, we propose two approaches, referred as CCNS-Greedy and CCNS-Energy, which target to reduce collision probability and to decrease energy consumption of secondary users when the system is underloaded. This, however, has one practical drawback in that the proposed CCNS method depends on PU and SU traffic characteristics such as inter-arrival time and service time, which might not be available in real scenario. We next illustrate that a MEAsurement-based Networks Selection (MEANS) scheme can be used to perform network selection for secondary users based on online measurement of PU collision probability of each network. We evaluated the performance based on extensive simulation, which conclusively shows that the proposed schemes achieve the best performance in terms of resulting PU collision probability, SU throughput, and SU energy consumption, when compared to both Random and Greedy strategies.

Intermittently Connected Wireless Networks (ICWN) or Delay/Disruption Tolerant Networks (DTN), have attracted attention from researchers because of their inherent characteristics, including long latency, low data rate, and intermittent connectivity. Extensive research has been conducted on ICWN, including the architecture, and routing. However, few researchers have investigated the performance of TCP in ICWN, especially when Epidemic Routing is used. In this paper, we first evaluate the performance of TCP in ICWN with Epidemic Routing. Our results show that the Epidemic Routing in ICWN degrades the performance of TCP because multicopy data packets cause duplicate ACKs, and in turn reduce the transmitting rate of TCP. Then an enhanced algorithm for TCP, named A-TCP/Reno is proposed to solve the above problem. A-TCP/Reno can avoid the duplicate ACK problem which is caused by Epidemic Routing. The simulation results show that A-TCP/Reno outperforms the TCP/Reno in ICWN with Epidemic Routing protocol.

Measurement studies have shown that uneven and dynamic usage patterns by the primary users of license based wireless communication systems often lead to temporal and spatial spectrum underutilization. This provides an opportunity for secondary users to tap into underutilized frequency bands provided that they are capable of cognitively accessing without colliding or impacting the performance of the primary users. When there are multiple networks with spare spectrum, secondary users can opportunistically choose the best network to access, subject to certain constraints. In cognitive radio systems, this is referred to as the network selection problem. In this paper, multiple network selection strategies namely, random, weighted, and greedy, are comprehensively evaluated. It is found that without adequate admission control, those methods cannot provide sufficient service protection for the primary users. Next, a Markov decision model is applied to obtain the maximum allowable arrival rate for secondary users subject to a target collision probability for the primary users. Based on this model, a Collision-Constrained Network Selection (CCNS) method is proposed that maximizes system throughput subject to a given collision probability. Simulations show that comparing to random, weighted, and greedy strategies CCNS achieves an improved performance in terms of system throughput and collision probability.

This paper investigates the performance of EPC-gloabl Generation-2 (Gen-2) ultra high frequency (UHF) radio frequency identification (RFID) protocol. Gen-2 protocol has a critical parameter Q that plays an important role in resolving tag collisions. Gen-2 protocol proposes an adaptive slot-count algorithm to adjust Q dynamically based on the type of replies from tags. In this paper, we define two performance metrics for tag identification: Query Success Rate (QSR) and tag identification speed (TIS). We establish a Discrete-Time Markov Chain (DTMC) model for the Gen-2 and accordingly obtain quantitative results of QSR and TIS. Extensive simulations validate our theoretical analysis and demonstrate that the number of tags has little impact on the performance. In other words, QSR and TIS do not nearly decrease even though the number of tags may be increasing. Our model for Gen-2 protocol is also useful to study the performance of other RFID protocols.

Radio frequency identification (RFID) provides a non-line-of-sight and contactless approach for object identification. But if there are multiple tags in the range of an RFID reader, tag collision can take place due to radio signal interference and therefore an anti-collision algorithm is required to

Congestion in wireless sensor networks not only causes packet loss, but also leads to excessive energy consumption. Therefore congestion in WSNs needs to be controlled in order to prolong system lifetime. In addition, this is also necessary to improve fairness and provide better quality of service (QoS), which is required by multimedia applications in wireless multimedia sensor networks. In this paper, we propose a novel upstream congestion control protocol for WSNs, called priority-based congestion control protocol (PCCP). Unlike existing work, PCCP innovatively measures congestion degree as the ratio of packet inter-arrival time along over packet service time. PCCP still introduced node priority index to reflect the importance of each sensor node. Based on the introduced congestion degree and node priority index, PCCP utilizes a cross-layer optimization and imposes a hop-by-hop approach to control congestion. We have demonstrated that PCCP achieves efficient congestion control and flexible weighted fairness for both single-path and multi-path routing, as a result this leads to higher energy efficiency and better QoS in terms of both packet loss rate and delay.

For analysis of the IEEE 802.11 distributed coordination function (DCF), one of the key assumptions commonly accepted is that every node always has at least one frame to transmit. In practice, however, this assumption may or may not be valid, particularly under unsaturated traffic conditions. In this paper, we assess the accuracy in using the traditional M/G/1 queueing model for the DCF as an alternative model at an individual node, and analyze its performance in unsaturated traffic conditions. Analytical and simulation results are compared to demonstrate a reasonable accuracy of the proposed approach for varying traffic loads at an individual node

Directional antenna has great potential to reduce power consumption in energy constrained wireless sensor networks. We consider a two-tier wireless sensor network where directional antenna is employed for upper-tier aggregation and forwarding nodes (AFNs). Existing flow routing solutions for maximizing network lifetime require each AFN to transmit multiple flows to different nodes at the same time, which we call multi-beam flow routing solution. In this paper, we show that it is possible to develop single-beam flow routing solution for nodes with directional antenna. More important, we show that the single-beam flow routing solution developed here is provably optimal in terms of network lifetime performance. This result is based on a novel technique to transform the optimal multi-beam flow routing into an equivalent single-beam flow routing solution. Numerical example illustrating how to obtain an optimal single-beam flow routing solution is also given.

We consider a two-tier wireless sensor network and focus on the flow routing problem for the upper tier aggregation and forwarding nodes (AFNs). Assuming each AFN is equipped with directional antennas for transmission, we are interested in how to perform flow routing at each node such that the network lifetime is maximized. We present a flow routing algorithm that provably has the following properties: (1) when the average source rate of each AFN is known a priori, the flow routing algorithm is optimal and gives maximum network lifetime performance; (2) when the average source rate of each AFN is unknown but is within a fraction, /spl epsiv/, of an estimated rate value, then the network lifetime given by the proposed flow routing algorithm is no more than 2/spl epsiv//(1-/spl epsiv/) from optimal. As a result, the proposed flow routing algorithm can provide predictable lifetime performance, even when the source bit rate can be time-varying.

Based on the current standardized IEEE 802.11 distributed coordination function (DCF) protocol, this paper proposes a new efficient collision resolution mechanism, called GDCF. Our main motivation is based on the observation that 802.11 DCF decreases the contention window to the initial value after each success transmission, which essentially assumes that each successful transmission is an indication that the system is under low traffic loading. GDCF takes a more conservative measure by halving the contention window size after c consecutive successful transmissions. This "gentle" decrease can reduce the collision probability, especially when the number of competing nodes is large. We compute the optimal value for c, and the numerical results from both analysis and simulation demonstrate that GDCF significantly improve the performance of 802.11 DCF including throughput, fairness, and energy efficiency. In addition, GDCF is flexible for supporting priority access by selecting different values of c for different traffic types; it is very easy to implement it, as it does not requires any changes in control message structure and access procedures in DCF.

Under the weak consistency paradigm, time-to-live (TTL)-based hierarchical caching systems are proposed to support Web content delivery. Within such systems, due to strictly hierarchical caching structure and linear TTL countdown function, a single user request may encounter consecutive cache miss events at cache servers of different levels in the hierarchy. This behavior, referred to as miss synchronization, is the main cause of a sudden increase in user-perceived response time. In this paper, we examine this undesirable behavior to gain a better understanding of its properties and characteristics. To mitigate this problem, we propose a family of nonlinear TTL countdown functions using a novel concept called extended lifetime. Performance analysis indicates that the proposed approach can effectively avoid miss synchronization in hierarchical caching systems. Further, a carefully-designed nonlinear countdown function can reduce cache miss ratio and user response time without any significant increase in outlived objects.

Active queue management (AQM) is an effective method to enhance congestion control, and to achieve tradeoff between link utilization and delay. The de facto standard, random early detection (RED), and most of its variants use queue length as a congestion indicator to trigger packet dropping. The proportional-integral (PI), use both queue length and traffic input rate as congestion indicators; effective stability model and practical design rules built on the TCP control model and abstracted AQM model reveal that such schemes enhance the stability of a system. In this paper, we propose an AQM scheme with fast response time, yet good robustness. The scheme, called loss ratio based RED (LRED), measures the latest packet loss ratio, and uses it as a complement to queue length in order to dynamically adjust packet drop probability. Employing the closed-form relationship between packet loss ratio and the number of TCP flows, this scheme is responsive even if the number of TCP flows varies significantly. We also provide the design rules for this scheme based on the well-known TCP control model. This scheme's performance is examined under various network configurations, and compared to existing AQM schemes, including PI, random exponentially marking (REM), and adaptive virtual queue (AVQ). Our simulation results show that, with comparable complexity', this scheme has short response time, better robustness, and more desirable tradeoff than PI, REM, and AQV, especially under highly dynamic network and heavy traffic load.

This paper proposes a rate-based active queue management algorithm or RAQM. It uses the aggregated traffic input rate to calculate packet drop probability according to an exponential rule. We analyze the stability and investigate practical implementation issues of the RAQM. Simulations are carried out to study RAQM performance and to compare with other AQM algorithms, in particular PI and REM schemes. The results demonstrate that RAQM achieves better stability and faster response as it can quickly regulate the queue length to the expected value with small overshoot. RAQM also obtains better tradeoff between link utilization and queuing delay, and obtains higher goodput with the same buffer size as in PI and REM schemes. Finally RAQM has O(1) complexity, thus is independent of the number of flows.

This paper studies the active queue management (AQM) in high-speed routers. One of the original and popularly implemented AQM algorithms is random early detection (RED). But it is hard to configure the parameters involved in RED. Although there are some new TCP-modeling based approaches to overcome this, they really show some instability under such dynamical environments with diverse connections (adaptive or non- adaptive, short or long), link rate, RTT, and buffer size. The major reason is that these approaches are primarily based on TCP model, which has some mismatches under dynamical environment. Since fuzzy-logic control does not need precise control model, it may be suitable for such environment. This paper designs an adaptive fuzzy-based control algorithm (AFRED), which computes the packet drop (or marking) probability according to pre-configured fuzzy logic using the instant queue length as input variable. The important feature of AFRED is that it also designs an adaptive mechanism to dynamically readjust the fuzzy rule so as to make AFRED itself extensively stable for many dynamic environments. Simulation results show that AFRED can effectively and stably control the queue length to the expected value or so. Compared with RED and PI algorithm, AFRED obtains higher goodput and stable queue length than RED and PI, even if introducing UDP flows.

We propose a novel integrated optical network switching architecture. The proposal offers an approach to signaling for the purpose of transport on an all-optical network of optical and nonoptical legacy network traffic. In order to provide effective end-to-end control and efficient transport services, new signaling and control techniques are required. Standard organizations such as Optical Interworking Forum (OIF) and Internet Engineering Task Force have developed interface methods between client and transport networks, as well as signaling processes for resource allocation. We propose a network controller, which implements interfaces for such integration in the intermediate future, as well as provides a feasible path for the long-term objective of all optical networking. Performance and capacity issues for these systems introduce new dimensions to the existing set of networking problems, since optical paths can now be set up in real-time. There are two main contributions in this paper: (1) functional composition of a network controller, which translates legacy signaling to optical connection signaling and path establishment and (2) determining when to issue an optical connection request based on the current network conditions such as link utilization, so that the integrated optical network can operate efficiently. Analytical approximations, as well as simulation results for call blocking performance are also presented.

Existing research demonstrates that an effective routing and wavelength assignment (RWA) strategy and a proper wavelength converter placement algorithm are the two primary vehicles for improving the blocking performance of wavelength-routed network. However, these two issues have largely been investigated, separately in that the existing RWA algorithms seldom consider the presence of wavelength conversion. We argue in this paper that any RWA algorithm needs to take into account the underlying wavelength conversion for two reasons: (1) wavelength converter placement is usually done at a much earlier stage during capacity planning; and (2) one of the key advantages of an all-optical network is its reconfigurability in that the network topology can be changed through routing and wavelength assignment. We propose a weighted least-congestion routing and first-fit wavelength assignment (WLCR-FF) RWA algorithm in conjunction with a heuristic wavelength converter placement algorithm called minimum blocking probability first (MBPF) that considers both the distribution of free wavelengths and the lengths of each route jointly. Using both analysis and simulation, we carry out extensive studies to compare the performance of the proposed algorithms over a variety of topologies. The results demonstrate that the proposed WLCR-FF algorithm can achieve much better blocking performance than static routing, fixed-alternate routing and least-loaded routing algorithms, in the environment of sparse or/and full wavelength conversion.

Web caching or web proxy has been considered as the prime vehicle of coping with the ever-increasing demand for information retrieval over the Internet, the WWW being a typical example. Existing work on web proxy has primarily focused on content based caching; relatively less attention has been given to the development of proper placement strategies for the potential web proxies in the Internet. In this paper, we argue that the placement of web proxies is critical to the performance and further investigates the optimal placement policy of web proxies for a target web server in the Internet. The objective is to optimize a given performance measure for the target web server subject to system resources and traffic pattern. Specifically, we are interested in finding the optimal placement of multiple web proxies (M) among potential sites (N) under a given traffic pattern. We show this can be modeled a dynamic programming problem. We further obtain the optimal solution for the tree topology using O(N/sup 3/M/sup 2/) time.

Multimedia traffic measurements for determining spatial correlation in videoteleconference sessions over a CSMA/CD LAN are performed and the results are presented in this paper. Since packet arrival streams are both correlated and bursty, we present the analysis of the cross-correlation characteristics between the number of arriving audio and video packet batches in discrete-time slots. The results of this experimental study can be extended to WAN environments such as ATM. If cross-correlation among monomedia streams is not properly taken into account, it can severely impact network performance.

A two-node asynchronous transfer mode (ATM) network is considered. Several video sources are assumed multiplexed at the source node. Five alternative algorithms for bandwidth allocation to video sources are considered using: static-slot assignment, buffer-population-based dynamic slot assignment, first-come-first-serve slot assignment and rate-based dynamic slot assignment. The average cell delay and the coefficient of variation of the delay for the five algorithms are determined by computer simulation and compared. It is concluded that the adaptive slot assignment algorithm and the buffer-population-based dynamic slot assignment algorithm are suitable for packet video in ATM networks.>