Thejaswini M’s research while affiliated with Indian Institute of Technology Hyderabad and other places

Advancement of mobile phone based new sensing paradigm like opportunistic and participatory crowd sensing has lead to increase in both multimedia and scalar sensor data traffic over wireless networks. In opportunistic crowd sensing, there are more chances of missing required mobile phones sensor data due to unpredictable mobility nature of users. Analysis of scheduling schemes under realistic human mobility models has become an important issue for pervasive sensing applications specifically for mobile phone based crowd sensing. This paper refers to a weighted scheduling framework for collecting mobile phone sensor data under Levy Walk mobility model. The proposed method uses duration of stay of mobile phone users as one of the important parameter to improve the scheduling performance in terms of reducing the rate of missing of mobile nodes and thereby increasing the rate of collection of required sensor data. The simulation results show that for improving the scheduling performance in opportunistic crowd sensing, high weight value should be given for duration of stay parameter, when mobile nodes stay within the data collection region for more than schedule iteration time with high probability.

Smart phones or mobile phones enabled with global positioning system (GPS), different types of sensors, and communication technologies have become ubiquitous application development platform for Internet of Things (IoT) and new sensing technologies. Improving sensing area coverage, reducing overlap of sensing area, and energy consumption are important issues under mobile phone sensing. This paper presents human mobility-based mobile phone sensors sampling algorithm. Human mobility patterns and geographical constraints have an impact on performance of mobile phone sensing applications. The real-outdoor location traces of volunteers, collected using GPS-enabled mobile phones are used for performance analysis of proposed work. The proposed mobile phone sensor sampling algorithm considers velocity of human mobility as an important parameter for improving sensing area coverage and reduction of energy consumption. To an extent overlap between sensing area coverage is allowed to overcome, the reduction of sensor data samples caused by spatial regularities of human mobility. The performance is analyzed and evaluated by considering general regular sampling and proposed sampling method for mobile phone sensing activity. The results show that for normal human walking velocity ( 1.5 m/s) proposed mobile phone sensor sampling algorithm performs better in terms of sensing area coverage and reduction of battery energy consumption for mobile phone sensing activity.

Mobile phones or smart phones equipped with different communication technologies and sensors have become pervasive application development platform for opportunistic and human-centric sensing. Optimisation of battery energy consumption and opportunistic sensing coverage are important issues under mobile phone sensing. This paper proposes a simple sampling algorithm based on human-walk velocity for mobile phone sensing. We analyse the impact of human-walk velocity on battery energy consumption and spatial coverage for mobile phone sensing by considering general regular sampling of sensors and proposed sampling method. When Levy walk mobility parameter α = 1, the proposed sampling algorithm shows better performance in terms of both spatial coverage and reduction of battery energy consumption for mobile phone sensing activity.

Unstable link connectivity due to dynamic mobility nature of mobile phone users and error prone wireless link quality increases end-to-end delay for mobile phone based opportunistic network applications. This problem becomes more worse in the presence of large amount of data transmission, like multimedia data. This paper refers to Levy walk based multi-hop data forwarding protocol called Data Transmission Time and Human Walk Velocity (DTT-HWV) for Opportunistic Mobile Phone Sensor Networks (OMPSN). This paper, in particular evaluates the performance of proposed protocol in terms of end-to-end waiting time to receive data, which is an important QoS requirement for data transmission in opportunistic networks. The proposed protocol DTT-HWV reduces end-to-end waiting time to receive data compared to Random Progress (RP) data forwarding method in presence of low battery power and high path loss. Obtained results are helpful in designing and building of large scale data retrieval services for opportunistic networks involving humans in the communication network loop.