Fariza Sabrina

Processing resource scheduling in programmable networks

Programmable network paradigm allows the execution of active applications in routers or switches to provide more flexibility to traditional networks, and richer services for users. In this paper, we discuss issues in designing resource schedulers for processing engines in programmable networks. One of the key problems in programmable networks is the inability to determine execution times of packets from information in headers for scheduling which is in contrast to using packet length in transport resources scheduling. Therefore, this paper focuses on developing CPU scheduling algorithms that could schedule CPU resource adaptively, fairly, and efficiently among all the competing flows. In this paper, we present two scheduling algorithms that could resolve the problem of prior determination of CPU requirement of the data packet. One of the proposed packet scheduling algorithm is called start time weighted fair queueing that does not require packet processing times in advance and the other one is called prediction based fair queueing which uses a prediction algorithm to estimate CPU requirements of packet and it then schedules the packets according to that. The effectiveness of these algorithms in achieving fairness and providing delay guarantee is shown through analysis and simulation work.

Scheduling resources in programmable and active networks based on adaptive estimations

In active and programmable networks, packet processing could be accomplished in the router within the data path. For efficient resource allocation in such networks, the packet scheduling schemes should consider multiple resources such as CPU and memory in addition to the bandwidth to improve overall performance. The inherent unpredictability of processing times of active packets poses a significant challenge in CPU scheduling. It has been identified that unlike bandwidth scheduling, prior estimation of CPU requirements of a packet is very difficult since it is platform dependent and it also depends on processing load at the time of execution and operating system scheduling etc. This paper presents an adaptive solution for estimating the processing requirements of active flows efficiently and accurately. The estimation process has been used in our composite scheduling algorithm called CBCS/sup WFQ/ to estimate processing requirement. The performances of the estimation process for our composite scheduler have been analyzed through simulation works.

A novel resource scheduling algorithm for QoS-aware services on the Internet

The popularity and availability of Internet connection has opened up the opportunity for network-centric collaborative work that was impossible a few years ago. Contending traffic flows in this collaborative scenario share different kinds of resources such as network links, buffers, and router CPU. The goal should hence be overall fairness in the allocation of multiple resources rather than a specific resource. In this paper, firstly, we present a novel QoS-aware resource scheduling algorithm called Weighted Composite Bandwidth and CPU Scheduler (WCBCS), which jointly allocates the fair share of the link bandwidth as well as processing resource to all competing flows. WCBCS also uses a simple and adaptive online prediction scheme for reliably estimating the processing times of the incoming data packets. Secondly, we present some analytical results, extensive NS-2 simulation work, and experimental results from our implementation on Intel IXP2400 network processor. The simulation and implementation results show that our low complexity scheduling algorithm can efficiently maximise the CPU and bandwidth utilisation while maintaining guaranteed Quality of Service (QoS) for each individual flow.

Adaptive Rate Control for Aggregated VoIP Traffic

This paper presents a novel mechanism for dynamically adapting the quality of congestion controlled voice over IP (VoIP) applications on the Internet in real time. The system uses our proposed variable bit rate speech codec called Speex, which can dynamically adjust the encoding bit rate (and hence the speech quality) based on both the feedback information about the network congestion and the instantaneous speech properties. Our extensive NS2 simulation results prove that the proposed system indeed provides highest quality speech while maximising the bandwidth utilisation and reducing the network congestion.

A novel architecture for resource management in active networks using a directory service

This paper presents a framework for resource management in highly dynamic active networks. The goal is to allocate and manage active node resources in an efficient way while ensuring effective utilization of network and supporting load balancing. The framework supports co-existence of active and non-active nodes and proposes a novel Directory Service (DS) architecture that can be used to discover the suitable active nodes in the Internet and for selecting best network path (end-to-end) and reserving the resources along the selected path. Intranode and inter-node resource management are facilitated through the DS, while within an active node the framework implements the composite scheduling algorithm to schedule memory, CPU and bandwidth to solve the combined resource scheduling problems. In addition, a flexible active node Knowledge base system has been introduced in order to resolve the challenging problem of determining the CPU requirement of the incoming packets.

Rate and delay controlled core networks: An experimental demonstration

Growing demand for streaming, voice and interactive gaming applications emphasize the importance of quality of service (QoS) provisioning in the Internet, particularly the need for maximum end-to-end delay guarantee. Current methods of QoS provisioning have either scalability concerns or cannot guarantee end-to-end delay with acceptable packet loss unless bandwidth is over-provisioned. While low jitter guarantee is required for streaming applications, maximum end-to-end delay is also required for VoIP and interactive games. We propose, analyze the stability and demonstrate the viability of three combined rate and end-to-end delay controls. The stability analysis is done on a fluid network model with greedy flows showing that all controls are globally asymptotically stable without information time lags and one of them is also globally asymptotically stable with arbitrary time lags; however it substantivally under-utilizes the network. Another control, which numerically demonstrates stability with arbitrary time lags, is implemented in edge and core routers of our WAN-in-Lab with long haul links. The prototype implementation confirms its viability and its advantage over the Differentiated Service architecture. The viability of the two other controls is shown by detailed NS2 packet-based simulations of an eight-node real core network.

Priority Based Dynamic Rate Control for VoIP Traffic

This paper presents a novel mechanism for dynamic rate control of prioritised Voice Over IP (VoIP) traffic in real time. The system uses our proposed variable bit rate speech codec called Speex, which can dynamically adjust the encoding bit rate (and hence the voice quality) based on the feedback information about the network congestion, flow priority, and the instantaneous speech properties. Our extensive NS2 simulation results along with results from ITU-T standard of speech quality evaluation tool (PESQ) show that the proposed system indeed provides highest quality speech while maximising the bandwidth utilisation and reducing the network congestion.

Design, Analysis, and Implementation of a Novel Low Complexity Scheduler for Joint Resource Allocation

Over the past decade, the problem of fair bandwidth allocation among contending traffic flows on a link has been extensively researched. However, as these flows traverse a computer network, they share different kinds of resources (e.g., links, buffers, router CPU). The ultimate goal should hence be overall fairness in the allocation of multiple resources rather than a specific resource. Moreover, conventional resource scheduling algorithms depend strongly upon the assumption of prior knowledge of network parameters and cannot handle variations or lack of information about these parameters. In this paper, we present a novel scheduler called the composite bandwidth and CPU scheduler (CBCS), which jointly allocates the fair share of the link bandwidth as well as processing resource to all competing flows. CBCS also uses a simple and adaptive online prediction scheme for reliably estimating the processing times of the incoming data packets. Analytically, we prove that CBCS is efficient, with a per-packet work complexity of O(1). Finally, we present simulation results and experimental outcomes from a real-world implementation of CBCS on an Intel IXP 2400 network processor. Our results highlight the improved performance achieved by CBCS and demonstrate the ease with which it can be implemented on off-the-shelf hardware

Design, Analysis and Implementation of a Novel Multiple Resource Scheduler

Over the past decade, the problem of achieving fair bandwidth allocation on a link shared by multiple traffic flows has been extensively researched. However, as these flows traverse a computer network, they share many different kinds of resources, such as links, buffers, and router CPU. The ultimate goal should hence be overall fairness in the allocation of multiple resources rather than a single specific resource such as link bandwidth. In this paper, we present a novel scheduler, called prediction-based composite fair queuing (PCFQ), which jointly allocates the fair share of the link bandwidth and processing resources to all competing flows. We derive the worst-case delay bound, the work complexity, and the relative fairness bound for the PCFQ scheduler and show that it outperforms a system consisting of separate bandwidth and CPU schedulers. We further present simulation results which illustrate the improved performance characteristics achieved by PCFQ. We also demonstrate that our composite scheduler can be easily implemented on an off-the-shelf network processor such as the Intel IXP 2400. Experimental results from the IXP 2400 implementation highlight the effectiveness and high performance of this algorithm in a real-world system.

Implementation and performance analysis of a packet scheduler on a programmable network processor

The problem of achieving fairness in the allocation of the bandwidth resource on a link shared by multiple flows of traffic has been extensively researched over the last decade. However, as these flows traverse a computer network, they share many different kinds of resources such as links, processor cycles, buffers and battery power, a critical resource in mobile devices. The ultimate goal should hence be overall fairness in the allocation of multiple resources rather than a single specific resource such as link bandwidth. In our earlier work we have presented a novel scheduler called prediction-based composite fair queueing (PCFQ), which jointly allocates the fair share of the link bandwidth as well as processing resource to all competing flows. Our scheme also uses a simple and adaptive online prediction scheme for reliably estimating the execution times of the incoming data packets. We have demonstrated via simulation experiments that PCFQ can provide much improved quality of service (QoS) guarantees as compared to separate bandwidth and processor schedulers. With the rapid increase in the capacity of transmission links, the ease with which a scheduler can be implemented in real hardware systems gains paramount importance. In this paper we concentrate on the design and implementation of the PCFQ scheduler in a programmable router. We demonstrate that our scheduler can be easily implemented on an off-the-shelf network processor such as the Intel IXP 2400 board. We also validate our design by carrying out extensive experiments and demonstrate the improved performance achieved by the PCFQ scheduler. The experimental results from the IXP 2400 implementation highlight the effectiveness and high performance of this algorithm in a real world system