Abstract
Novel network systems need to be carefully evaluated before their actual deployments in developing regions. However, large-scale network experiment is a challenging task. Simulations, emulations, and real-world testbeds all have their advantages and disadvantages. In this paper we present LiteLab, a light-weight platform specialized for large-scale networking experiments. We cover in detail its design, key features, and architecture. We also perform an extensive evaluation of Lite-Lab's performance and accuracy and show that it is able to both simulate network parameters with high accuracy, and also able to scale up to very large networks. LiteLab is flexible, easy to deploy, and allows researchers to perform large-scale network experiments with a short development cycle. We have used LiteLab for many different kinds of network experiments and are planning to make it available for others to use as well.
Highlights
Deploying network systems in developing regions is a very difficult task, even for those mature and well-tested systems
There are both technical and non-technical barriers such as extreme environment, inefficient transportation, lack of local technicians, limited equipments, poor infrastructure, and many other socio-economical challenges. These challenges grow even larger when we try to apply cutting-edge networking technologies to tackle the specific issues in developing regions. ”Trial and error” method will fail in such a context due to its high cost. To reduce both investment risk and maintenance overhead, we need to obtain a comprehensive understanding of the overall system behaviours before its actual deployment, which requires us to efficiently explore a large parameter space
We present how we evaluate various aspects of LiteLab and how we adapted it to get around practical issues
Summary
Deploying network systems in developing regions is a very difficult task, even for those mature and well-tested systems There are both technical and non-technical barriers such as extreme environment, inefficient transportation, lack of local technicians, limited equipments, poor infrastructure, and many other socio-economical challenges. These challenges grow even larger when we try to apply cutting-edge networking technologies to tackle the specific issues in developing regions. ”Trial and error” method will fail in such a context due to its high cost To reduce both investment risk and maintenance overhead, we need to obtain a comprehensive understanding of the overall system behaviours before its actual deployment, which requires us to efficiently explore a large parameter space (to model real-world dynamics).
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