Pricing and resource allocation for LTE video multicast: In light of increasing video traffic from mobile devices but restricted wireless spectrum, ISPs are considering new ways of efficiently delivering content to users. In cases with spatial and temporal locality of content requests, video multicast using LTE eMBMS is one possible solution. One major challenge for the ISP is how to ensure profitability of providing multicast service, while still maintaining good QoS for all users. The ISP can receive revenue from the content provider, who subsidizes the multicast delivery cost, and the end-user, who pays for unicast data plan. The ISP must balance these two competing factors to allocate resources for multicast and unicast users. We examine the interaction between (a) ISP revenue maximization and (b) unicast user QoS. We model the ISP’s revenue sources and formulate the revenue maximization problem, and provide an analytic solution. This informs our analysis of the impact of the content provider’s pricing, the users’ cellular conditions, and the number of multicast users.
AVIS: Scheduling for adaptive videos over cellular networks: As the growth of mobile video trafﬁc outpaces that of cellular network speed, industry is adopting HTTP-based adaptive video streaming technology which enables dynamic adaptation of video bit-rates to match changing network conditions. However, recent measurement studies have observed problems in fairness, stability, and efﬁciency of resource utilization when multiple adaptive video ﬂows compete for bandwidth on a shared wired link. Through experiments and simulations, we conﬁrm that such undesirable behavior manifests itself in cellular networks as well. To overcome these problems, we design an in-network resource management framework, AVIS, that schedules HTTP-based adaptive video ﬂows on cellular networks. AVIS effectively manages the resources of a cellular base station across adaptive video ﬂows. We implement a prototype system of AVIS and evaluate it on both a WiMAX network testbed and a LTE system simulator to show its efﬁcacy and scalability.[paper][slides]
QAVA: Quota-aware video adaptation: Two emerging trends of Internet applications, video traffic becoming dominant and usage-based pricing plans becoming prevalent, are at odds with each other. On one hand, videos, especially on high-resolution devices (e.g., iPhone 5, iPad, Android tablets), consume much more data than other types of traffic; for instance, 15 min of low bitrate YouTube videos per day uses 1 GB a month. On the other hand, gone are the days of unlimited data plans; instead, wireless ISPs such as AT&T and Verizon are imposing data caps on consumers. Given this conflict, a natural question to ask is: Can the consumer stay within her monthly data quota without suffering a noticeable drop in video quality? My research in this area focuses on designing algorithms to maximize the user's quality of experience and stay under the data quota, by leveraging the user's past data consumption profile and video preferences.[paper][slides][presentation]
Chen J, Ghosh A, Chiang M, "Mechanisms for Quota-Aware Video Adaptation," book chapter: Smart Data Pricing, ed. Sen S, Joe-Wong C, Ha S, Chiang M, John Wiley, forthcoming in 2013.
Chen J, Mahindra R, Khojastepour A, Rangarajan S, Chiang M, "Scheduling Framework for Adaptive Video Delivery over Cellular Networks," ACM MobiCom, 2013. [pdf]
Chen J, Sen S, Dorsey D, Chiang M, "A Framework for Energy-efficient Adaptive Jamming of Adversarial Communications," CISS, 2013. [pdf]
Chen J, Ghosh A, Magutt J, Chiang M, "QAVA: Quota-Aware Video Adaptation," ACM CoNEXT, 2012. [pdf]
Gorlatova M, Noorbhaiwala Z, Skolnik A, Sarik J, Szczodrak M, Chen J, Zapas M, Carloni L, Kinget P, Kymissis I, Rubenstein S, Zussman G, "Prototyping Energy Harvesting Active Networked Tags: Phase II MICA Mote-based Devices (demo)," ACM MobiCom, 2010. [pdf]
Gorlatova M, Sharma T, Shrestha D, Chen J, Skolnik A, Piao D, Kinget P, Kymissis J, Rubenstein D, Zussman G, "Prototyping Energy Harvesting Active Networked Tags (EnHANTs) with MICA2 Motes (demo)," IEEE SECON, 2010 June. [pdf]
Chan ME, Chen J, Chiang V, Liu XS, Baik AD, Lu XL, Huo B, Guo XE, “A Novel 3D Coculture Trabecular Bone Explant Model for the Study of Bone Adaptation and Mechanotransduction," World Congress on Bioengineering, July. [pdf]
Chan ME, Chen J, Chiang V, Liu XS, Baik AD, Lu XL, Huo B, Guo XE, "Roles of Mechanical Stimuli and Gap Junctional Communication in Long-Term Coculture of 3D Trabecular Bone Explants," Transactions of the Orthopaedic Research Society, vol. 34, paper #53, 2009. [pdf]
Last updated Nov. 18, 2013