Internet protocol television (IPTV) will be the killer application for the next-generation Internet and will provide exciting new revenue opportunities for service providers. However, to deploy IPTV services with a full quality of service (QoS) guarantee, many underlying technologies must be further studied. This article serves as a survey of IPTV services and the underlying technologies. Technical challenges also are identified.

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Internet Protocol Television (IPTV): The Killer Application for the Next-Generation Internet

The generalized Langevin equation describes processes in a mechanical system with both deterministic and random forces which have comparable magnitudes (i.e., neither the deterministic nor random part can be neglected) and the random force is a transformed white noise. Examples of such processes are well known in physics. In this chapter, we use integral operators with Riemannian parallel translation in order to study the Langevin equations arising in geometric mechanics. Note that in the case under consideration the trajectories of the process are a.s. smooth. This makes the analysis of such systems technically much simpler than that of the general ones studied in Chap. 4.

The Langevin Equation

Synthetic aperture is a method used to improve radar resolution in azimuth or in the direction of the velocity vector of platform. This resolution is comparable with the one that is obtained by a very large physical antenna. This chapter focuses on the optimal aspect of the synthetic aperture processing and its uses in air-borne and space-borne imaging radar applications. The synthetic aperture effect is obtained by displacement of the platform or target. Focused synthetic aperture processing takes into account the variation of target angular position with radar velocity during illumination. The received signal is expressed in relation to the transmitted signal and target range. Unfocused synthetic aperture processing is performed by a simple spectral analysis that is matched to targets located at infinity. The processing of unfocused synthetic aperture is optimum when illumination time is very short. If the illumination time is sufficiently long, the received signal is linearly frequency modulated. Target illumination time depends on antenna aperture, platform velocity, and the distance between the radar and the target. A pulse waveform of low repetition frequency is generally used in synthetic aperture radar (SAR). The time and Doppler ambiguities are related to the value of the repetition period.

15 – synthetic aperture radar

Utility or on-demand computing, a provisioning model where a service provider makes computing infrastructure available to customers as needed, is becoming increasingly common in enterprise computing systems. Realizing this model requires making dynamic, and sometimes risky, resource provisioning and allocation decisions in an uncertain operating environment to maximize revenue while reducing operating cost. This paper develops an optimization framework wherein the resource provisioning problem is posed as one of sequential decision making under uncertainty and solved using a limited lookahead control scheme. The proposed approach accounts for the switching costs incurred during resource provisioning and explicitly encodes risk in the optimization problem. Simulations using workload traces from the Soccer World Cup 1998 web site show that a computing system managed by our controller generates up to 20% more profit than a system without dynamic control while incurring low control overhead.

Risk-aware limited lookahead control for dynamic resource provisioning in enterprise computing systems

Mobile cloud computing (MCC) improves the computational capabilities of resource-constrained mobile devices. On the other hand, the mobile users demand a certain level of quality-of-service (QoS) provisioning while they use services from the cloud, even if the interfacing gateway changes due to the mobility of the users. In this paper, we identify, formulate, and address the problem of QoS-guaranteed bandwidth shifting and redistribution among the interfacing gateways for maximizing their utility. Due to node mobility, bandwidth shifting is required for providing QoS-guarantee to the mobile nodes. However, shifting alone is not always sufficient for maintaining QoS-guarantee because of varying spectral efficiency across the associated channels, coupled with the corresponding protocol overhead involved with the computation of utility. We formulate bandwidth redistribution as a utility maximization problem, and solve it using a modified descending bid auction. In the proposed scheme, named as AQUM, each gateway aggregates the demands of all the connecting mobile nodes and makes a bid for the required amount of bandwidth. We investigate the existence of Nash equilibrium (NE) in the proposed solution. Theoretically, we deduce the maximum and minimum selling prices of bandwidth, and prove the convergence of AQUM. Simulation results establish the correctness of the proposed algorithm.

QoS-Guaranteed Bandwidth Shifting and Redistribution in Mobile Cloud Environment

In this paper, the maximal capacity of the data network link has attempted to be exploited by using the dynamic allocation strategy. We propose a new methodology based on the economic models for competing traffic classes (classes of sessions) in packet networks. As the demand for network services accelerates, users' satisfaction to the service level might decrease due to the congestion at the network nodes. To prevent this, efficient allocation of a networks resources, such as available bandwidth and switch capacity, is needed. By using the so-called user profile as well as the utility (e.g., data rate) functions, it is possible to allocate data rates and other utilities using the arbitrary number of QoS classes, say $0.01,…, $10.

Optimal link allocation and revenue maximization

This paper presents a new methodology based on economic models to provide Quality of Service (QoS) guarantees to competing traffic classes (classes of sessions) in packet networks. We consider an economic model of a packet network where resources are priced. As the demand for network services accelerates, users' satisfaction to the service level might decrease due to congestion at the network nodes. To prevent this, efficient allocation of network resources, such as available bandwidth and switch capacity, is needed. By using so-called user profile as well as utility (e.g. data rate) functions, it is possible to allocate data rates and other utilities using arbitrary number of QoS classes, say 0.01,..., 10. Maximal capacity of the data network infrastructure is exploited by using a dynamic allocation strategy.

QoS aware adaptive pricing for network services

Different applications, such as voice over IP and video-on-demand, need different quality of service parameters (e.g., guaranteed bandwidth, delay, and latency) from the networks. The customers with different needs pay different prices to the service provider, who must share resources in a plausible way. In a router, packets are queued using a multi-queue system, where each queue can correspond to one service class. This paper presents an adaptive weighted fair queue based algorithm for channel allocation. The weights in gradient type algorithms are adapted by using revenue as a target function.

Adaptive weighted fair scheduling method for channel allocation

Comparison and analysis of the revenue-based adaptive queuing models

As the Web is becoming a medium widely used as a preferential channel for critical information exchange, business, and e-commerce, it is necessary to enable differentiated service (DiffServ) mechanisms not only at the network but also at the Web server level. We present a new service differentiation mechanism (arrival-related dynamic partitioning) for cluster-based network servers. We demonstrate by simulation that it can guarantee that customers with higher priority classes receive better service than ones with lower priority classes and achieve the basic goals with service differentiation, especially when the system is heavily loaded with not enough server resources to allocate. An admission control mechanism is also provided to prevent a Web site from being overwhelmed by excessive user requests.

Jyrki Joutsensalo

Papers

Optimal link allocation and revenue maximization

QoS aware adaptive pricing for network services

Adaptive weighted fair scheduling method for channel allocation

Comparison and analysis of the revenue-based adaptive queuing models

A new mechanism for supporting differentiated services in cluster-based network servers