This paper aims to identify and understand whether national policy initiatives, regulatory measures, or governance practices increase a developing nation's mobile broadband affordability. For this purpose, a cross-national multiple regression analysis of non-OECD countries is used. The results revealed that when controlling for wealth, education and other factors, competition to provide mobile services, financial investment in ICTs, and income inequality are all important variables for determining mobile broadband affordability. Findings suggest that service providers and other stakeholders are still recouping the cost of deploying the infrastructure necessary to provide mobile services, and have not yet achieved the economies of scale required for the price of mobile broadband to begin to fall, at least in the developing world. This paper provides contributions to academia, industry, and policymakers.

In cluster computing, power and cooling represent a significant cost compared to the hardware itself. This is of special concern in the cloud, which provides access to large numbers of computers. We examine the use of ARM-based clusters for low-power, high performance computing. This work examines two likely use-modes: (i) a standard dedicated cluster, and (ii) a cluster of pre-configured virtual machines in the cloud. A 40-node department-level cluster based on an ARM Cortex-A9 is compared against a similar cluster based on an Intel Core2 Duo, in contrast to a recent similar study on just a 4-node cluster. For the NAS benchmarks on 32-node clusters, ARM was found to have a power efficiency ranging from 1.3 to 6.2 times greater than that of Intel. This is despite Intel's approximately five times greater performance. The particular efficiency ratio depends primarily on the size of the working set relative to L2 cache. In addition to energy-efficient computing, this study also emphasizes fault tolerance: an important ingredient in high performance computing. It relies on two recent extensions to the DMTCP checkpoint-restart package. DMTCP was extended (i) to support ARM CPUs, and (ii) to support check pointing of the Qemu virtual machine in user-mode. DMTCP is used both to checkpoint native distributed applications, and to checkpoint a network of virtual machines. This latter case demonstrates the ability to deploy pre-configured software in virtual machines hosted in the cloud, and further to migrate cluster computation between hosts in the cloud.

This research is motivated by large-scale pervasive sensing applications. We examine the benefits and costs of caching data for such applications. We propose and evaluate several approaches to querying for, and then caching data in a sensor field data server. We show that for some application requirements (i.e., when delay drives data quality), policies that emulate cache hits by computing and returning approximate values for sensor data yield a simultaneous quality improvement and cost savings. This win-win is because when system delay is sufficiently important, the benefit to both query cost and data quality achieved by using approximate values outweighs the negative impact on quality due to the approximation. In contrast, when data accuracy drives quality, a linear trade-off between query cost and data quality emerges. We also identify caching and lookup policies for which the sensor field query rate is bounded when servicing an arbitrary workload of user queries. This upper bound is achieved by having multiple user queries share the cost of a single sensor field query. Finally, we demonstrate that our results are robust to the manner in which the environment being monitored changes using models for two different sensing systems.

In this paper we present a performance study of memory reference behavior in network protocol processing, using an Internet-based protocol stack implemented in the x-kernel running in user space on a MIPS R4400-based Silicon Graphics machine. We use the protocols to drive a validated execution-driven architectural simulator of our machine. We characterize the behavior of network protocol processing, deriving statistics such as cache miss rates and percentage of time spent waiting for memory. We also determine how sensitive protocol processing is to the architectural environment, varying factors such as cache size and associativity, and predict performance on future machines.We show that network protocol cache behavior varies widely, with miss rates ranging from 0 to 28 percent, depending on the scenario. We find instruction cache behavior has the greatest effect on protocol latency under most cases, and that cold cache behavior is very different from warm cache behavior. We demonstrate the upper bounds on performance that can be expected by improving memory behavior, and the impact of features such as associativity and larger cache sizes. In particular, we find that TCP is more sensitive to cache behavior than UDP, gaining larger benefits from improved associativity and bigger caches. We predict that network protocols will scale well with CPU speeds in the future.

Security and privacy are growing concerns in the Internet community, due to the Internet's rapid growth and the desire to conduct business over it safely. This desire has led to the advent of several proposals for security standards, such as secure IP, secure HTTP, and the Secure Socket Layer. All of these standards propose using cryptographic protocols such as DES and RSA. Thus, the need to use encryption protocols is increasing. Shared-memory multiprocessors make attractive server platforms, for example as secure World-Wide Web servers. These machines are becoming more common, as shown by recent vendor introductions of platforms such as SGI's Challenge, Sun's SPARCCenter, and DEC's AlphaServer. The spread of these machines is due both to their relative ease of programming and their good price/performance. This paper is an experimental performance study that examines how encryption protocol performance can be improved by using parallelism. We show linear speedup for several different Internet-based cryptographic protocol stack running on a symmetric shared-memory multiprocessor using two different approaches to parallelism.

Over the next several years the performance demands on globally available information servers are expected to increase dramatically. These servers must be capable of sending and receiving data over hundreds or even thousands of simultaneous connections. In this paper, we show that connection-level parallel protocols (where different connections are processed in parallel) running on a shared-memory multiprocessor can deliver high network bandwidth across a large number of connections.We experimentally evaluate connection-level parallel implementations of both TCP/IP and UDP/IP protocol stacks. We focus on three questions in our performance evaluation: how throughput scales with the number of processors, how throughput changes as the number of connections increases, and how fairly the aggregate bandwidth is distributed across connections. We show how several factors impact performance: the number of processors used, the number of threads in the system, the number of connections assigned to each thread, and the type of protocols in the stack (i.e., TCP versus UDP).Our results show that with careful implementation connection-level parallel protocol stacks scale well with the number of processors, and deliver high throughput which is, for the most part, sustained as the number of connections increases. Maximizing the number of threads in the system yields the best overall throughput. However, the best fairness behavior is achieved by matching the number of threads to the number of processors and scheduling connections assigned to threads in a round-robin manner.

A crucial problem facing the designers and deployers of future high-speed networks is providing applications with quality of service (QOS) guarantees. For soft real-time applications, which are delay sensitive but loss tolerant, delay distribution is an important QOS measure of interest. In this paper we study (through simulation) the end-to-end delay distribution seen by individual sessions under simple first-come first-served (FCFS) multiplexing in a network model with two significant features: (1) all traffic is connection-oriented, (2) cross traffic along routes is representative of that seen by calls in a moderately sized wide area network (i.e., less than 100 switches). We compare these delay distributions with the worst case point-valued analytic delay bounds predicted by three different techniques for providing such bounds (two of which require a more sophisticated link-level scheduling policy). We also consider the per-hop delay distributions seen as a session progresses deeper into the network and determine the sensitivity of these delay distributions to the manner in which the interfering traffic is modeled. Finally, we use our delay distribution results to examine the tradeoff between the QOS requested by a call, the manner in which the QOS guarantee is provided, and the number of calls that are admitted at the requested QOS.