A Study of Quality of Service Communication for High-Speed Packet-Switching Computer Sub-Networks

In this thesis, we analyze various factors that affect quality of service (QoS) communication in high-speed, packet-switching sub-networks. We hypothesize that sub-network-wide bandwidth reservation and guaranteed CPU processing power at endpoint systems for handling data traffic are indispensable to achieving hard end-to-end quality of service. Different bandwidth reservation strategies, traffic characterization schemes, and scheduling algorithms affect the network resources and CPU usage as well as the extent that QoS can be achieved. In order to analyze those factors, we design and implement a communication layer. Our experimental analysis supports our research hypothesis. The Resource ReSerVation Protocol (RSVP) is designed to realize resource reservation. Our analysis of RSVP shows that using RSVP solely is insufficient to provide hard end-to-end quality of service in a high-speed sub-network. Analysis of the IEEE 802.lp protocol also supports the research hypothesis

On scheduling input queued cell switches

Output-queued switching, though is able to offer high throughput, guaranteed delay and fairness, lacks scalability owing to the speed up problem. Input-queued switching, on the other hand, is scalable, and is thus becoming an attractive alternative. This dissertation presents three approaches toward resolving the major problem encountered in input-queued switching that has prohibited the provision of quality of service guarantees. First, we proposed a maximum size matching based algorithm, referred to as min-max fair input queueing (MFIQ), which minimizes the additional delay caused by back pressure, and at the same time provides fair service among competing sessions. Like any maximum size matching algorithm, MFIQ performs well for uniform traffic, in which the destinations of the incoming cells are uniformly distributed over all the outputs, but is not stable for non-uniform traffic. Subse-quently, we proposed two maximum weight matching based algorithms, longest normalized queue first (LNQF) and earliest due date first matching (EDDFM), which are stable for both uniform and non-uniform traffic. LNQF provides fairer service than longest queue first (LQF) and better traffic shaping than oldest cell first (OCF), and EDDEM has lower probability of delay overdue than LQF, LNQF, and OCF. Our third approach, referred to as store-sort-and-forward (SSF), is a frame based scheduling algorithm. SSF is proved to be able to achieve strict sense 100% throughput, and provide bounded delay and delay jitter for input-queued switches if the traffic conforms to the (r, T) model

Resource Management in Multimedia Networked Systems

Error-free multimedia data processing and communication includes providing guaranteed services such as the colloquial telephone. A set of problems have to be solved and handled in the control-management level of the host and underlying network architectures. We discuss in this paper \u27resource management\u27 at the host and network level, and their cooperation to achieve global guaranteed transmission and presentation services, which means end-to-end guarantees. The emphasize is on \u27network resources\u27 (e.g., bandwidth, buffer space) and \u27host resources\u27 (e.g., CPU processing time) which need to be controlled in order to satisfy the Quality of Service (QoS) requirements set by the users of the multimedia networked system. The control of the specified resources involves three actions: (1) properly allocate resources (end-to-end) during the multimedia call establishment, so that traffic can flow according to the QoS specification; (2) control resource allocation during the multimedia transmission; (3) adapt to changes when degradation of system components occurs. These actions imply the necessity of: (a) new services, such as admission services, at the hosts and intermediate network nodes; (b) new protocols for establishing connections which satisfy QoS requirements along the path from send to receiver(s), such as resource reservation protocol; (c) new control algorithms for delay, rate and error control; (d) new resource monitoring protocols for reporting system changes, such as resource administration protocol; (e) new adaptive schemes for dynamic resource allocation to respond to system changes; and (f) new architectures at the hosts and switches to accommodate the resource management entities. This article gives an overview of services, mechanisms and protocols for resource management as outlined above

Renegotiation based dynamic bandwidth allocation for selfsimilar VBR traffic

The provision of QoS to applications traffic depends heavily on how different traffic types are categorized and classified, and how the prioritization of these applications are managed. Bandwidth is the most scarce network resource. Therefore, there is a need for a method or system that distributes an available bandwidth in a network among different applications in such a way that each class or type of traffic receives their constraint QoS requirements. In this dissertation, a new renegotiation based dynamic resource allocation method for variable bit rate (VBR) traffic is presented. First, pros and cons of available off-line methods that are used to estimate selfsimilarity level (represented by Hurst parameter) of a VBR traffic trace are empirically investigated, and criteria to select measurement parameters for online resource management are developed. It is shown that wavelet analysis based methods are the strongest tools in estimation of Hurst parameter with their low computational complexities, compared to the variance-time method and R/S pox plot. Therefore, a temporal energy distribution of a traffic data arrival counting process among different frequency sub-bands is considered as a traffic descriptor, and then a robust traffic rate predictor is developed by using the Haar wavelet analysis. The empirical results show that the new on-line dynamic bandwidth allocation scheme for VBR traffic is superior to traditional dynamic bandwidth allocation methods that are based on adaptive algorithms such as Least Mean Square, Recursive Least Square, and Mean Square Error etc. in terms of high utilization and low queuing delay. Also a method is developed to minimize the number of bandwidth renegotiations to decrease signaling costs on traffic schedulers (e.g. WFQ) and networks (e.g. ATM). It is also quantified that the introduced renegotiation based bandwidth management scheme decreases heavytailedness of queue size distributions, which is an inherent impact of traffic self similarity. The new design increases the achieved utilization levels in the literature, provisions given queue size constraints and minimizes the number of renegotiations simultaneously. This renegotiation -based design is online and practically embeddable into QoS management blocks, edge routers and Digital Subscriber Lines Access Multiplexers (DSLAM) and rate adaptive DSL modems

Simplicial Homology for Future Cellular Networks

Simplicial homology is a tool that provides a mathematical way to compute the connectivity and the coverage of a cellular network without any node location information. In this article, we use simplicial homology in order to not only compute the topology of a cellular network, but also to discover the clusters of nodes still with no location information. We propose three algorithms for the management of future cellular networks. The first one is a frequency auto-planning algorithm for the self-configuration of future cellular networks. It aims at minimizing the number of planned frequencies while maximizing the usage of each one. Then, our energy conservation algorithm falls into the self-optimization feature of future cellular networks. It optimizes the energy consumption of the cellular network during off-peak hours while taking into account both coverage and user traffic. Finally, we present and discuss the performance of a disaster recovery algorithm using determinantal point processes to patch coverage holes

Burst switched optical networks supporting legacy and future service types

Focusing on the principles and the paradigm of OBS an overview addressing expectable performance and application issues is presented. Proposals on OBS were published over a decade and the presented techniques spread into many directions. The paper comprises discussions of several challenges that OBS meets, in order to compile the big picture. The OBS principle is presented unrestricted to individual proposals and trends. Merits are openly discussed, considering basic teletraffic theory and common traffic characterisation. A more generic OBS paradigm than usual is impartially discussed and found capable to overcome shortcomings of recent proposals. In conclusion, an OBS that offers different connection types may support most client demands within a sole optical network layer

Cloud Workload Allocation Approaches for Quality of Service Guarantee and Cybersecurity Risk Management

It has become a dominant trend in industry to adopt cloud computing --thanks to its unique advantages in flexibility, scalability, elasticity and cost efficiency -- for providing online cloud services over the Internet using large-scale data centers. In the meantime, the relentless increase in demand for affordable and high-quality cloud-based services, for individuals and businesses, has led to tremendously high power consumption and operating expense and thus has posed pressing challenges on cloud service providers in finding efficient resource allocation policies. Allowing several services or Virtual Machines (VMs) to commonly share the cloud\u27s infrastructure enables cloud providers to optimize resource usage, power consumption, and operating expense. However, servers sharing among users and VMs causes performance degradation and results in cybersecurity risks. Consequently, how to develop efficient and effective resource management policies to make the appropriate decisions to optimize the trade-offs among resource usage, service quality, and cybersecurity loss plays a vital role in the sustainable future of cloud computing. In this dissertation, we focus on cloud workload allocation problems for resource optimization subject to Quality of Service (QoS) guarantee and cybersecurity risk constraints. To facilitate our research, we first develop a cloud computing prototype that we utilize to empirically validate the performance of different proposed cloud resource management schemes under a close to practical, but also isolated and well-controlled, environment. We then focus our research on the resource management policies for real-time cloud services with QoS guarantee. Based on queuing model with reneging, we establish and formally prove a series of fundamental principles, between service timing characteristics and their resource demands, and based on which we develop several novel resource management algorithms that statically guarantee the QoS requirements for cloud users. We then study the problem of mitigating cybersecurity risk and loss in cloud data centers via cloud resource management. We employ game theory to model the VM-to-VM interdependent cybersecurity risks in cloud clusters. We then conduct a thorough analysis based on our game-theory-based model and develop several algorithms for cybersecurity risk management. Specifically, we start our cybersecurity research from a simple case with only two types of VMs and next extend it to a more general case with an arbitrary number of VM types. Our intensive numerical and experimental results show that our proposed algorithms can significantly outperform the existing methodologies for large-scale cloud data centers in terms of resource usage, cybersecurity loss, and computational effectiveness