Scalable Localization with Mobility Prediction for Underwater Sensor Networks

Abstract

Abstract-Due to adverse aqueous environments, non-negligible node mobility and large network scale, localization for large-scale mobile underwater sensor networks is very challenging. In this paper, by utilizing the predictable mobility patterns of underwater objects, we propose a scheme, called Scalable Localization scheme with Mobility Prediction (SLMP), for underwater sensor networks. In SLMP, localization is performed in a hierarchical way, and the whole localization process is divided into two parts: anchor node localization and ordinary node localization. During the localization process, every node predicts its future mobility pattern according to its past known location information, and it can estimate its future location based on its predicted mobility pattern. Anchor nodes with known locations in the network will control the whole localization process in order to balance the tradeoff between localization accuracy, localization coverage and communication cost. We conduct extensive simulations, and our results show that SLMP can greatly reduce localization communication cost while maintaining relatively high localization coverage and localization accuracy.

An efficient geo-routing aware MAC protocol for underwater acoustic networks

“…Luckily, a couple of localization algorithms [11][12][13][14] have been designed for underwater acoustic networks, which make geo-routing possible. Geo-routing protocols which are based on the nodes location have been gaining significant attention because they perform stateless routing which allows their routing cost to be very low.…”

“…These protocols do not need dedicated route discovery and forward packets directly based on the nodes locations. Since location information is indispensable for many aquatic applications [10][11][12][13][14], these protocols do not cause much extra cost and are very efficient from the routing perspective.…”

“…With these techniques, GOAL is energy-efficient and provides high end-to-end reliability. Another remarkable feature is that GOAL can work in mobile underwater acoustic networks with localization services such as SLMP [14].…”

Recent Advances in Future Mobile Multimedia Networks

“…The base station selection procedure should be done, by controlling and adapting QoE performance indicators which represent service integrity, such as throughput, delay, jitter, packet loss, bit error rate (BER), peak signal-to-noise ratio (PSNR), structural similarity (SSIM), video quality metric (VQM), and mean opinion score (MOS)-related metrics Zinner et al (2010). In addition, buffer and caching mechanisms, together with mobility prediction and session context transfer approaches, must be integrated in order to provide seamless mobile multimedia handover in future wireless networks Klein & Klaue (2009) Zhou et al (2010).…”

Time Synchronization with Oceanic Movement Pattern in Underwater Wireless Networks

“…따라서 센서노드의 움직임은 일 정한 반경 내에서만 허용된다. 그리고 해양 유체역 학적 분석과 노드움직임의 실제적 측정결과는 해수 운동이 물체에 주기적인 힘을 가한다는 것을 증명 한다 [7][8][9] . …”