Energy-Aware Load Balancing in Content Delivery Networks

Internet-scale distributed systems such as content delivery networks (CDNs) operate hundreds of thousands of servers deployed in thousands of data center locations around the globe. Since the energy costs of operating such a large IT infrastructure are a significant fraction of the total operating costs, we argue for redesigning CDNs to incorporate energy optimizations as a first-order principle. We propose techniques to turn off CDN servers during periods of low load while seeking to balance three key design goals: maximize energy reduction, minimize the impact on client-perceived service availability (SLAs), and limit the frequency of on-off server transitions to reduce wear-and-tear and its impact on hardware reliability. We propose an optimal offline algorithm and an online algorithm to extract energy savings both at the level of local load balancing within a data center and global load balancing across data centers. We evaluate our algorithms using real production workload traces from a large commercial CDN. Our results show that it is possible to reduce the energy consumption of a CDN by more than 55% while ensuring a high level of availability that meets customer SLA requirements and incurring an average of one on-off transition per server per day. Further, we show that keeping even 10% of the servers as hot spares helps absorb load spikes due to global flash crowds with little impact on availability SLAs. Finally, we show that redistributing load across proximal data centers can enhance service availability significantly, but has only a modest impact on energy savings

Cross-layer energy-efficient schemes for multimedia content delivery in heterogeneous wireless networks

The wireless communication technology has been developed focusing on fulfilling the demand in various parts of human life. In many real-life cases, this demand directs to most types of commonly-used rich-media applications which – with diverse traffic patterns - often require high quality levels on the devices of wireless network users. Deliveries of applications with different patterns are accomplished using heterogeneous wireless networks using multiple types of wireless network structure simultaneously. Meanwhile, content deliveries with assuring quality involve increased energy consumption on wireless network devices and highly challenge their limited power resources. As a result, many efforts have been invested aiming at high-quality and energy-efficient rich-media content deliveries in the past years. The research work presented in the thesis focuses on developing energy-aware content delivery schemes in heterogeneous wireless networks. This thesis has four major contributions outlined below: 1. An energy-aware mesh router duty cycle management scheme (AOC-MAC) for high-quality video deliveries over wireless mesh networks. AOC-MAC manages the sleep-periods of mesh devices based on link-state communication condition, reducing their energy consumption by extending their sleep-periods. 2. An energy efficient routing algorithm (E-Mesh) for high-quality video deliveries over wireless mesh networks. E-Mesh evolves an innovative energy-aware OLSR-based routing algorithm by taking energy consumption, router position and network load into consideration. 3. An energy-aware multi-flow-based traffic load balancing scheme (eMTCP) for multi-path content delivery over heterogeneous wireless networks. The scheme makes use of the MPTCP protocol at the upper transport layer of network, allowing data streams to be delivered across multiple consequent paths. Meanwhile, this benefit of MPTCP is also balanced with energy consumption awareness by partially off-loading traffic from the paths with higher energy cost to others. 4. A MPTCP-based traffic-characteristic-aware load balancing mechanism (eMTCP-BT) for heterogeneous wireless networks. In eMTCP-BT, mobile applications are categorized according to burstiness level. eMTCP-BT increases the energy efficiency of the application content deliveries by performing a MDP-based distribution of traffic delivery via the available wireless network interfaces and paths based on the traffic burstiness level

Self-Sustaining Caching Stations: Towards Cost-Effective 5G-Enabled Vehicular Networks

In this article, we investigate the cost-effective 5G-enabled vehicular networks to support emerging vehicular applications, such as autonomous driving, in-car infotainment and location-based road services. To this end, self-sustaining caching stations (SCSs) are introduced to liberate on-road base stations from the constraints of power lines and wired backhauls. Specifically, the cache-enabled SCSs are powered by renewable energy and connected to core networks through wireless backhauls, which can realize "drop-and-play" deployment, green operation, and low-latency services. With SCSs integrated, a 5G-enabled heterogeneous vehicular networking architecture is further proposed, where SCSs are deployed along roadside for traffic offloading while conventional macro base stations (MBSs) provide ubiquitous coverage to vehicles. In addition, a hierarchical network management framework is designed to deal with high dynamics in vehicular traffic and renewable energy, where content caching, energy management and traffic steering are jointly investigated to optimize the service capability of SCSs with balanced power demand and supply in different time scales. Case studies are provided to illustrate SCS deployment and operation designs, and some open research issues are also discussed.Comment: IEEE Communications Magazine, to appea

Technical considerations towards mobile user QoE enhancement via Cloud interaction

This paper discusses technical considerations of a Cloud infrastructure which interacts with mobile devices in order to migrate part of the computational overhead from the mobile device to the Cloud. The aim of the interaction between the mobile device and the Cloud is the enhancement of parameters that affect the Quality of Experience (QoE) of the mobile end user through the offloading of computational aspects of demanding applications. This paper shows that mobile user’s QoE can be potentially enhanced by offloading computational tasks to the Cloud which incorporates a predictive context-aware mechanism to schedule delivery of content to the mobile end-user using a low-cost interaction model between the Cloud and the mobile user. With respect to the proposed enhancements, both the technical considerations of the cloud infrastructure are examined, as well as the interaction between the mobile device and the Cloud

Living on the Edge: The Role of Proactive Caching in 5G Wireless Networks

This article explores one of the key enablers of beyond $4$G wireless networks leveraging small cell network deployments, namely proactive caching. Endowed with predictive capabilities and harnessing recent developments in storage, context-awareness and social networks, peak traffic demands can be substantially reduced by proactively serving predictable user demands, via caching at base stations and users' devices. In order to show the effectiveness of proactive caching, we examine two case studies which exploit the spatial and social structure of the network, where proactive caching plays a crucial role. Firstly, in order to alleviate backhaul congestion, we propose a mechanism whereby files are proactively cached during off-peak demands based on file popularity and correlations among users and files patterns. Secondly, leveraging social networks and device-to-device (D2D) communications, we propose a procedure that exploits the social structure of the network by predicting the set of influential users to (proactively) cache strategic contents and disseminate them to their social ties via D2D communications. Exploiting this proactive caching paradigm, numerical results show that important gains can be obtained for each case study, with backhaul savings and a higher ratio of satisfied users of up to $22\%$ and $26\%$, respectively. Higher gains can be further obtained by increasing the storage capability at the network edge.Comment: accepted for publication in IEEE Communications Magazin