The randomized server problem

In the k-server problem there are k ≥ 2 identical servers which are located at k points in a metric space M. If there is a request to a point r ∈ M, one of the servers must be moved to the request point in order to serve this request. The cost of this service is the distance between the points where the server resided before the service and after the service. A k-server algorithm A must decide which server should be moved at each step. The goal of A is to minimize the total service cost. Competitiveness makes sense as a concept when A lacks timely access to all input data. We consider the version of the problem where requests must be served online , i.e., the algorithm must decide which server to move without knowledge of future requests. Randomization is a strong tool to derive algorithms with better competitiveness; The main contributions of this thesis are: (1) An explicit detailed proof of the 2-competitiveness of the Random Slack Algorithm, which has never been given before. We note that Random Slack is a trackless algorithm. (2) An essay-style description of a new concept called the knowledge state approach, which has recently been developed by Bein, Larmore, and Reischuk. (3) We give optimally competitive randomized algorithms for 2 and 3 cache paging with few bookmarks. We note that the paging problem is a special case of the server problem, and that it is desirable to minimize the number of bookmarks, as such bookmarks pose a considerable challenge in real world applications such as cache management of pages on the world wide web; Furthermore, the thesis summarizes a number of basic results for both the randomized and the deterministic server problem

Joint Energy Efficient and QoS-aware Path Allocation and VNF Placement for Service Function Chaining

Service Function Chaining (SFC) allows the forwarding of a traffic flow along a chain of Virtual Network Functions (VNFs, e.g., IDS, firewall, and NAT). Software Defined Networking (SDN) solutions can be used to support SFC reducing the management complexity and the operational costs. One of the most critical issues for the service and network providers is the reduction of energy consumption, which should be achieved without impact to the quality of services. In this paper, we propose a novel resource (re)allocation architecture which enables energy-aware SFC for SDN-based networks. To this end, we model the problems of VNF placement, allocation of VNFs to flows, and flow routing as optimization problems. Thereafter, heuristic algorithms are proposed for the different optimization problems, in order find near-optimal solutions in acceptable times. The performance of the proposed algorithms are numerically evaluated over a real-world topology and various network traffic patterns. The results confirm that the proposed heuristic algorithms provide near optimal solutions while their execution time is applicable for real-life networks.Comment: Extended version of submitted paper - v7 - July 201

On the Benefit of Virtualization: Strategies for Flexible Server Allocation

Virtualization technology facilitates a dynamic, demand-driven allocation and migration of servers. This paper studies how the flexibility offered by network virtualization can be used to improve Quality-of-Service parameters such as latency, while taking into account allocation costs. A generic use case is considered where both the overall demand issued for a certain service (for example, an SAP application in the cloud, or a gaming application) as well as the origins of the requests change over time (e.g., due to time zone effects or due to user mobility), and we present online and optimal offline strategies to compute the number and location of the servers implementing this service. These algorithms also allow us to study the fundamental benefits of dynamic resource allocation compared to static systems. Our simulation results confirm our expectations that the gain of flexible server allocation is particularly high in scenarios with moderate dynamics