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Purdue CS 59000 - Computer

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51APRIL 2010Published by the IEEE Computer Society0018-9162/10/$26.00 © 2010 IEEE C OV E R F E AT U R ESAVING ENERGY FOR MOBILE SYSTEMSMobile systems, such as smart phones, have become the primary computing platform for many users. Various studies have identified longer battery lifetime as the most desired feature of such systems. A 2005 study of users in 15 countries3 found longer battery life to be more impor-tant than all other features, including cameras or storage. A survey last year by ChangeWave Research4 revealed short battery life to be the most disliked characteristic of Apple’s iPhone 3GS, while a 2009 Nokia poll showed that battery life was the top concern of music phone users.Many applications are too computation intensive to perform on a mobile system. If a mobile user wants to use such applications, the computation must be performed in the cloud. Other applications such as image retrieval, voice recognition, gaming, and navigation can run on a mobile system. However, they consume significant amounts of energy. Can offloading these applications to the cloud save energy and extend battery lifetimes for mobile users?Low-power design has been an active research topic for many years. In IEEE Xplore, searching “low” and “power” in the document title produces more than 5,000 results. There are four basic approaches to saving energy and ex-tending battery lifetime in mobile devices:• Adopt a new generation of semiconductor technol-ogy. As transistors become smaller, each transistor consumes less power. Unfortunately, as transistors become smaller, more transistors are needed to pro-vide more functionalities and better performance; as a result, power consumption actually increases.Cloud computing1 is a new paradigm in which computing resources such as processing, memory, and storage are not physically pres-ent at the user’s location. Instead, a service provider owns and manages these resources, and users access them via the Internet. For example, Amazon Web Services lets users store personal data via its Simple Storage Service (S3) and perform computations on stored data using the Elastic Compute Cloud (EC2). This type of computing provides many advantages for businesses—including low initial capital investment, shorter start-up time for new services, lower maintenance and operation costs, higher utilization through virtual-ization, and easier disaster recovery—that make cloud computing an attractive option. Reports suggest that there are several benefits in shifting computing from the desktop to the cloud.1,2 What about cloud computing for mobile users? The primary constraints for mobile computing are limited energy and wireless bandwidth. Cloud computing can provide energy savings as a service to mobile users, though it also poses some unique challenges.The cloud heralds a new era of computing where application services are provided through the Internet. Cloud computing can enhance the computing capability of mobile systems, but is it the ultimate so-lution for extending such systems’ battery lifetimes?Karthik Kumar and Yung-Hsiang Lu, Purdue UniversityCLOUD COMPUTING FOR MOBILE USERS: CAN OFFLOADING COMPUTATION SAVE ENERGY?Authorized licensed use limited to: Purdue University. Downloaded on April 10,2010 at 16:10:45 UTC from IEEE Xplore. Restrictions apply.C OV E R F E AT U R ECOMPUTER 52Computation CCommunication DNeveroffloadAlwaysoffloadDependsonbandwidthBa simple analysis for this decision. Suppose the computation requires C instructions. Let S and M be the speeds, in instructions per second, of the cloud server and the mobile system, respectively. The same task thus takes C/S seconds on the server and C/M seconds on the mobile system. If the server and mobile system ex-change D bytes of data and B is the network bandwidth, it takes D/B seconds to transmit and receive data. The mobile system consumes, in watts, Pc for computing, Pi while being idle, and Ptr for sending and receiving data. (Trans-mission power is generally higher than reception power, but for the purpose of this analysis, they are identical.)If the mobile system performs the computation, the energy consumption is Pc × (C/M). If the server performs the computation, the energy consumption is [Pi × (C/S)] + [Ptr × (D/B)]. The amount of energy saved isPc× CM−  Pi× CS−  Ptr× DB. (1)Suppose the server is F times faster—that is, S = F × M. We can rewrite the formula asCM× Pc−PiF− Ptr×DB. (2)Energy is saved when this formula produces a positive number. The formula is positive if D/B is sufficiently small compared with C/M and F is sufficiently large. The values of M, Pi, Pc, and Pth are parameters specific to the mobile system. For example, an HP iPAQ PDA with a 400-MHz (M = 400) Intel XScale processor has the following values: Pc ≈ 0.9 W, Pi ≈ 0.3 W, and Ptr ≈ 1.3 W. If we use a four-core server, with a clock speed of 3.2 GHz, the server speedup F may be given by (S/M) ≈ [(3.2 × 1,024 × 4 × X)/400], where X is the speedup due to additional memory, more aggressive pipelining, and so forth. If we assume X = 5, we obtain the value of F ≈ 160. The value of F can increase even more with cloud com-puting if the application is parallelizable, since we can offload computation to multiple servers. If we assume that F = 160, Equation 2 becomesC400× 0.9−0.3160−1.3×DB≈ 0.00225×C()−1.3×DB. (3)For offloading to break even, we equate Equation 3 to zero and obtainBo≈577.77 ×DC, (4) where Bo is the minimum bandwidth required for offload-ing to save energy, determined by the ratio of (D/C). If (D/C) is low, then offloading can save energy. Thus, as Figure 1 shows, offloading is beneficial when large amounts of computation C are needed with relatively small amounts of communication D.• Avoid wasting energy. Whole systems or individual components may enter standby or sleep modes to save power.• Execute programs slowly. When a processor’s clock speed doubles, the power consumption nearly oc-tuples. If the clock speed is reduced by half, the execution time doubles, but only one quarter of the energy is consumed.• Eliminate computation all together. The mobile system does not perform the computation; instead, computa-tion is performed somewhere else, thereby


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Purdue CS 59000 - Computer

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