2 research outputs found
A New Competitive Ratio for Network Applications with Hard Performance Guarantee
Online algorithms are used to solve the problems which need to make decisions
without future knowledge. Competitive ratio is used to evaluate the performance
of an online algorithm. This ratio is the worst-case ratio between the performance
of the online algorithm and the offline optimal algorithm. However, the competitive
ratios in many current studies are relatively low and thus cannot satisfy the
need of the customers in practical applications. To provide a better service, a practice
for service provider is to add more redundancy to the system. Thus we have
a new problem which is to quantify the relation between the amount of increased
redundancy and the system performance.
In this dissertation, to address the problem that the competitive ratio is not
satisfactory, we ask the question: How much redundancy should be increased to
fulfill certain performance guarantee? Based on this question, we will define a
new competitive ratio showing the relation between the system redundancy and
performance of online algorithm compared to offline algorithm. We will study
three applications in network applications. We propose online algorithms to solve
the problems and study the competitive ratio. To evaluate the performances, we
further study the optimal online algorithms and some other commonly used algorithms
as comparison.
We first study the application of online scheduling for delay-constrained mobile
offloading. WiFi offloading, where mobile users opportunistically obtain data
through WiFi rather than through cellular networks, is a promising technique to greatly improve spectrum efficiency and reduce cellular network congestion. We
consider a system where the service provider deploys multiple WiFi hotspots to
offload mobile traffic with unpredictable mobile users’ movements. Then we study
online job allocation with hard allocation ratio requirement. We consider that jobs
of various types arrive in some unpredictable pattern and the system is required to
allocate a certain ratio of jobs. We then aim to find the minimum capacity needed
to meet a given allocation ratio requirement. Third, we study online routing in
multi-hop network with end-to-end deadline. We propose reliable online algorithms
to schedule packets with unpredictable arriving information and stringent
end-to-end deadline in the network