Tunable Energy Parameter to Improve Energy Efficiency in Mobile Applications
Smartphones have now become a dominant computing device for a wide variety of mobile applications. For such a device, the main challenge is to provide the best performance, while utilizing energy efficiently. Given that energy is a major constraint in smartphones, a tool that allows the user to automatically control the device battery usage by various applications will be beneficial. To build such a tool, it is important to study the trade-off between performance and energy. In this paper, we provide a detailed analysis and evaluation of storage energy consumption on Android devices. We have evaluated the energy consumption of sequential and random I/O and SQLite operations on two filesystems supported by Android -- Ext4 and Flash Friendly File System (F2FS). Our experiments reveal that the energy consumed by random writes in F2FS is 40% less, whereas it is 20% higher for random reads as compared to ext4. This opens up avenues for improving the random read performance in F2FS for Android. Our work is to explore ways of dynamically optimizing the amount of data to be sequentialized, to maintain a balance between performance and energy consumption as specified by application requirements.
Benchmarking SQLite is Rocket Science!
SQLite, which is an embedded database widely used for storage in the server and mobile contexts, is gaining popularity as an application-level benchmark both in industry and in the systems research community. However, benchmarking SQLite is tricky: its performance varies greatly based on a number of configuration parameters. We show that changing just one parameter in SQLite can change performance by 11.8X, and that changing multiple parameters can lead up to a 28X difference in performance. We investigate various parameters that could affect SQLite performance and state the importance and necessity of a standard configuration for SQLite benchmarking.
A Reinforcement Learning Approach to Optimize Downloads Over Mobile Networks
The aim of this work is to propose and investigate a multiphase request model of the MERLIN protocol using Reinforcement Learning and compare its efficiency against a single phase version. We show via comprehensive empirical and real trace simulations that the multiphase request protocol performs better than single phase protocol and the baseline server push method.
MERLIN protocol for Single-Phase Downloads over Random Duration Links in Mobile Networks
Short range communication is attracting a lot of interest these days due to its utility in vehicular safety and infotainment applications as well as for improving the capacity of cellular networks. A fundamental problem in this domain is to maximize the amount of useful content downloaded by a client from a server over an encounter that lasts a random amount of time. Assuming that the distribution of link duration is known or estimated a priori based on historical as well as real-time measurements, we propose a protocol called MERLIN (Maximum Expected download over Random LINks), a single-phase file request protocol that is provably optimal.
Smart and Secure Monitoring of Industrial Environments using IoT
The steep surge in industrialization and poor strategies used in controlling industrial pollution has resulted in degradation in the quality of environment around us. An IoT framework was proposed, to smartly connect industrial surroundings. Our proposed framework helps in monitoring the level of pollutants, particulate matter and effluents released into the environment, notifying concerned authorities whenever their permissible level surpasses. Also we smartly connect the houses in close vicinity, so that precautionary measures can be taken to evacuate people in times of unexpected leakages.
Reducing DNS Cache Poisoning Attacks
The increasing attacks on The Domain Name System (DNS) and the problems faced in deploying Domain Name System Security Extensions (DNSSEC) on a large scale, result in the need of a simple, and a practical approach to safeguard the DNS. We present an efficient approach to significantly reduce the success rate of DNS cache poisoning attacks, namely Shift Key(S-Key) based domain name encoding scheme and the Bi-Query scheme.
Approximate max-flow min-multicut theorem for series parallel graphs.
In a series parallel graph, it is known that if the capacity of each cut exceeds the demand across it by a factor of 2, then multi commodity flow is routable. There is no theorem known, when one is interested in computing the maximum integral flow in SP graph. Hence, the problem was to find an approximate max-flow min-cut theorem and thus provide a 2 approximation algorithm to compute multicuts in SP graph.
AData structures and Algorithm is the heart of computer Science. The best way to understand complex data structures is to see them in action. Thus, an android application has been developed using the PhoneGap framework, where in there are interactive animations for a variety of data structures and algorithms. This could act as a quick and handy reference to understand any data structure.