Energy efficient routers are important and promising devices in the roadmap toward green networking. In this paper, we explore this topic with a traffic aware design that can automatically adapt the router's energy consumption to the network traffic in real time with transitions at the scale from microseconds to nanoseconds. In this paper, we make three contributions. First, we propose an energy efficient router architecture using frequency scaling, which is extended from the contemporary line card architecture of the router. Second, we prototype our architecture on a gigabit NetFPGA platform, which extends a router design on that platform to dynamically work at six frequencies. Then, we discuss the implementation in detail and present a per-packet-based power consumption model from real-world measurements. Third, we further propose four algorithms, which efficiently and automatically adapt power grades under the methodology of periodical and threshold-based scaling. Our experiments are carried out on two platforms, a NetFPGA prototype for feasible scenarios and a simulator for other scenarios in excess of the NetFPGA port limit with parameters synthetically generated to the real-world measurement. Experimental results show that approximately 25% power can be saved with our architecture and algorithms. Conclusions are also given to summarize our findings.

Energy efficient routers are a promising step forward in the road-map towards energy efficient networking. In this paper, we use gigabit routers to measure and evaluate the impacts of green technologies in different scenarios. These programmable NetFPGA based routers come with the inbuilt feature of frequency scaling which can reduce the operational frequency of the board by half from 125MHz to 62.5MHz. Router power consumption is compared for standard and low frequency modes with different numbers of activated ports. Perpacket and per-byte energy costs in different cases with different packet sizes are measured and analyzed to evaluate the effects of frequency adjustment. Finally, a simple energy model for real traffic is proposed and evaluated. This paper reveals the internal power usage of a gigabit router at the granularity of packet, and header and payload byte level, and offers the reader a clear understanding of the potential power savings at different operational router frequencies, for different numbers of activated ports, various traffic loads and packet sizes, which would assist the green data center networks.

In the context of wireless user's increasing demands for better device power and battery management, this paper investigates some factors that can impact the power consumption on the energy consumption of mobile devices. The focus is on two factors when performing multimedia streaming: the impact of the traffic location within a WLAN; and the impact of the radio access network technology (WLAN, HSDPA, UMTS). The energy measurement results show that by changing the quality level of the multimedia stream the energy can be greatly conserved while the user perceived quality level is still acceptable. Moreover, by using the cellular interface much more energy is consumed (up to 61%) than by using the WLAN interface.

Energy conservation has become a critical issue around the world. In smart phones, battery power capabilities are not keeping up with the advances in other technologies (e.g., processing and memory) and are rapidly becoming a concern, especially in view of the growth in usage of energy-hungry mobile multimedia streaming. The deficiency in battery power and the need for reduced energy consumption provides motivation for researchers to develop energy efficient techniques in order to manage the power consumption in next-generation wireless networks. As there is little analysis in the literature on the relationship between the wireless environment and the mobile device energy consumption, this paper investigates the impact of network-related factors (e.g., network load and signal quality level) on the power consumption of the mobile device in the context of video delivery. This paper analyzes the energy consumption of an Android device and the efficiency of the system in several scenarios while performing video delivery (over UDP or TCP) on an IEEE 802.11g network. The results show that the network load and the signal quality level have a combined significant impact on the energy consumption. This analysis can be further used when proposing energy efficient adaptive multimedia and handover mechanisms.

Handover solutions ensuring seamless connectivity and high user-perceived quality of service for a given application context are essential for multi-mode wireless devices in heterogeneous wireless network environments. A critical handover step, the network selection decision, is automatically and transparently made in the user's terminal, aiming to keep the user “always best connected”. We propose Quantified Adaptive Delay Selection (QADS), a novel multi-user-aware handover algorithm that maintains high quality of service levels for mobile users performing handover in heterogeneous wireless network environments. QADS is a user-centric solution buildt on the IEEE 802.21 Media Independent Handover standard. It addresses the problem of multiple mobile nodes performing network selection independently, using the same selection algorithm. With innovative mechanisms based on adaptive contention and randomization, the algorithm increases overall user-perceived quality of service.

The demand for multimedia services is increasing and users expect rich services at high quality levels, even while on the move and connected via different wireless networks. This paper proposes a novel signal strength-based adaptive multimedia delivery mechanism (SAMMy) that makes use of the IEEE 802.11k standard when dynamically adjusting multimedia delivery based on estimated signal strength and actual loss rates, in order to increase user perceived quality for video streaming applications in WLAN. Location and time dimensions are used together with the receive signal strength estimations in order to predict the QoS characteristics along the user's path. The proposed mechanism is evaluated by simulation and compared with a non-adaptive multimedia delivery mechanism and with two other adaptive schemes, in terms of loss, throughput and Peak Signal to Noise Ratio (PSNR). The results show that the proposed signal strength-based adaptive multimedia delivery scheme outperforms the other schemes involved making more efficient use of the wireless network resources and increasing the user perceived quality.

Development in wireless access technologies and multihomed personal user devices is driving the way towards a heterogeneous wireless access network environment. Success in this arena will be reliant on the ability to offer an enhanced user experience. Users will plan to take advantage of the competition and always connect to the network which can best service their preferences for the current application. They will rely on intelligent network selection decision strategies to aid them in their choice. The contribution of this paper is to propose an intelligent utility-based strategy for network selection in this multi-access network scenario. A number of utility functions are examined which explore different user attitudes to risk for money and delay preferences related to their current application. For example we show that risk takers who are willing to pay more money get a better service.

This paper describes and formalises the service oriented heterogeneous wireless network environment (SOHWNE), the future service provision and delivery environment that supports ubiquitous user access anywhere at any time from diverse devices to a broad range of services. These services can be offered by third parties and can be accessed via one of many available networks. This paper also proposes and describes a novel algorithm for intelligent cost-oriented and performance-aware selection between available networks. This user-centric strategy focuses on the maximisation of consumer surplus when selecting the best available connection for transferring non real-time data, with user specified time constraints, in a user-centric SOHWNE

In future wireless and mobile environments it is likely that users will have access to multiple networks at the same time. Therefore there is a need to have mechanisms in place to decide which network is the most suitable for each user at each moment in time for every application that the user requires. We propose a user-centric solution where users choose the radio access network which meets their data transfer terms best. Naturally, each user wants timely quality data delivery at a low cost. In the radio environment data rates can never be guaranteed due to the unreliable nature of the radio links. The user network selection algorithm needs to predict the data rate on offer in each of the available networks and make the decision based on those predictions. This paper allows the user to select the network that will maximise the consumer surplus for non real-time data, while taking into account the delays