Vijay Sarathi Kesavan

Energy efficient network selection and seamless handovers in Mixed Networks

Network selection is the decision process for a mobile terminal to handover between homogeneous or heterogeneous networks. This handover decision can be either mobile or network initiated. Todays decision is mainly based on the received signal strength (RSS). In the future as the number of available networks increase the selection process must evaluate additional factors such as monetary cost, offered services, network conditions, required energy to operate in a network, system conditions, user and operators preferences. Upcoming IEEE or 3GPP standards provide facilities such as network maps, handover negotiation messages, network and client event reports and message exchange like handover triggers and handover negotiation. In this paper we investigate the use of a cost function to perform an optimal network selection using information provided by these standards, such as network coverage map or network properties. The cost function provides flexibility to balance different factors in the decision making, and our research is focused on improving both seamlessness and energy efficiency of the device and handovers. We evaluated our approach based on usage scenarios over WiFi, WiMax, and 3G networks using captured signal strength traces. The results of our simulations and early implementation show that our schemes select the optimal networks and handovers were triggered at appropriate times to increase overall network connectivity as compared to traditional triggering schemes, while at the same time optimizing energy consumption of multi-radio devices.

A smart triggering scheme to reduce service interruption during heterogeneous handovers

Multi-radio devices provide end-users the ability to achieve ubiquitous and seamless connectivity anytime, anywhere across heterogeneous networks. Minimal service disruption while a device roams across networks is key for a successful deployment. Todaypsilas roaming decisions are reactive and traditionally based on thresholds for signal strength or other radio properties, leading to undesirable handover delays. This paper introduces an Intel/BT client architecture to support seamless mobility for multi-radio devices and proposes a novel approach to predict when a device needs to take proactive actions to perform handovers. Significant improvement in reducing service discontinuity time is demonstrated by applying our approach to WiFi and WiMax networks. We also validate the architecture and algorithm benefits using our WiFi/WiMax multi-radio prototype in heterogeneous wireless network environments.

IEEE 802.21 Assisted Seamless and Energy Efficient Handovers in Mixed Networks

Network selection is the decision process for a mobile terminal to handoff between homogeneous or heterogeneous networks. With multiple available networks, the selection process must evaluate factors like network services/conditions, monetary cost, system conditions, user preferences etc. In this paper, we investigate network selection using a cost function and information provided by IEEE 802.21. The cost function provides flexibility to balance different factors in decision making and our research is focused on improving both seamlessness and energy efficiency of handovers. Our solution is evaluated using real WiFi, WiMax, and 3G signal strength traces. The results show that appropriate networks were selected based on selection policies, handovers were triggered at optimal times to increase overall network connectivity as compared to traditional triggering schemes, while at the same time the energy consumption of multi-radio devices for both on-going operations as well as during handovers is optimized.

Using predictive triggers to improve handover performance in mixed networks

End-users of multi-radio devices expect ubiquitous connectivity anytime and anywhere across heterogeneous networks. A minimal service disruption time while roaming across networks is key for successful deployments. Todays roaming decisions are reactive and traditionally based on thresholds for signal strength, missed beacons, or other properties, leading to undesirable handover delays. In this paper we propose a novel and energy efficient approach to predict when a device needs to take proactive actions to perform either a horizontal or vertical handover. The significant improvements our solution achieved in reducing service discontinuity time are demonstrated by applying our algorithms on WiFi and WiMax networks, in both enterprise and citywide wireless environments.