Next Generation Mobile and Ubiquitous Platforms

Mobile and Sensor Platform for Context Computing in Sensor-rich Mobile Environments

This work envisions a mobile device such as smartphone as a central gateway forming a personal sensor network (PSN) dynamically incorporating body-worn sensors and space-embedded sensors. Such a smartphone-centric personal sensor network will be a common computing platform shared by diverse ubiquitous applications that continuously monitors mobile user’s context. A key challenge is that the PSN as a common underlying platform should support a number of applications with highly scarce and dynamic resources of incorporated devices. To this end, we identify core functionalities of mobile and sensor platform to serve a number of futuristic applications, i.e., abstraction of pervasive resources and coordination of user interaction over open, mobile environments. Scale, heterogeneity, and power limitation of pervasive resources in such environments magnify the complexity of the abstraction. The platform should carefully orchestrate a number of distributed resources such as numerous sensors to facilitate application development and operation without suffering from the complexity. Also, for proper coordination of interactions between applications and users, it is critical to understand users’ contexts and diverse application requirements in a fine-grained manner. Accordingly, the mobile and sensor platform should provide suitable ways to support effective resource coordination and efficient situation-awareness and adaptive response.
As an initial effort to develop such a platform, first, we present a scalable and energy-efficient context monitoring framework, SeeMon. The advanced ubiquitous services for mobile individuals require continuous monitoring of personal contexts and surrounding situations that should be derived in real-time from numerous sensors. This is potentially a serious overhead for personal devices usually under resource limitation. As a general service provisioning framework, SeeMon supports the effective development and operation of the applications exploiting rich contexts through intuitive monitoring query semantics. Moreover, SeeMon employs a novel context monitoring approach that achieves a high degree of efficiency in computation and energy consumption. Second, we present an active resource orchestration framework for context monitoring, Orchestrator. Fully exploiting multiple alternative resource use options to process monitoring requests, it enables concurrent applications to share and utilize scarce and dynamic resources in a well-coordinated manner. On top of SeeMon and Orchestrator frameworks, multiple applications over the PSN can effectively understand users’ contexts with highly scarce and dynamic resources and react appropriately to serve the users. We implement and test a prototype system on multiple mobile devices such as smart phones and UMPC with a diverse set of sensors. Example applications are also developed based on the implemented system to evaluate the effectiveness of the frameworks. Results of the work so far have been published or accepted for publication in prestigious conferences and journals such as ACM/USENIX MobiSys 2008 (ACM/USENIX International Conference on Mobile Services, applications, and Systems, June 2008), IEEE PerCom 2010 (IEEE International Conference on Pervasive Computing and Communications, March 2010), IEEE TMC 2010 (IEEE Transactions on Mobile Computing, May 2010), CACM (Communications of the ACM).
Figure 1 Sensor-rich mobile environment for mobile context computing

Figure 2 Smartphones and sensor devices deployed for the prototype system

Figure 3 Context monitoring platform overview


Seungwoo Kang
Youngki Lee
Younghyun Ju
Chulhong Min
Jinwon Lee
Taiwoo Park


Seungwoo Kang, S.S. Iyengar, Youngki Lee, Jinwon Lee, Chulhong Min, Younghyun Ju, Taiwoo Park, Yunseok Rhee, Junehwa Song, “MobiCon: Mobile Context Monitoring Platform for Sensor-Rich Dynamic Environments”, Communications of ACM (To appear)
Seungwoo Kang, Jinwon Lee, Hyukjae Jang, Youngki Lee, Souneil Park, and Junehwa Song, “ A Scalable and Energy-efficient Context Monitoring Framework for Mobile Personal Sensor Networks “, IEEE Transactions on Mobile Computing (TMC), Vol. 9, No. 5, pp. 686-702, May 2010
Seungwoo Kang, Youngki Lee, Chulhong Min, Younghyun Ju, Taiwoo Park, Jinwon Lee, Yunseok Rhee, Junehwa Song, “Orchestrator: An Active Resource Orchestration Framework for Mobile Context Monitoring in Sensor-rich Mobile Environments“, in Proceedings of IEEE International Conference on Pervasive Computing and Communications (PerCom 2010), Mannheim, Germany, Mar.29-Apr.2 2010. (acceptance rate: 12%)
Seungwoo Kang, Jinwon Lee, Hyukjae Jang, Hyonik Lee, Youngki Lee, Souneil Park, Taiwoo Park, and Junehwa Song, “SeeMon: Scalable and Energy-efficient Context Monitoring Framework for Sensor-rich Mobile Environments“, in Proceedings of the 6th International Conference on Mobile Systems, Applications, and Services (MobiSys 2008), Colorado, USA, June 2008. (acceptance rate: 22/123 = 18%)
Kyungmin Cho, Inseok Hwang, Seungwoo Kang, Byoungjip Kim, Jinwon Lee, SangJeong Lee, Souneil Park, Yunseok Rhee, Junehwa Song, “HiCon: A Hierarchical Context Monitoring and Composition Framework for Next Generation Context-aware Services“, IEEE Network, Vol. 22, No. 4, July 2008

Comments are closed.