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As the user base for ubiquitous technology expands to developing regions, the likelihood of disparity between the lived experience of design team members (developers, designers, researchers, etc.) and end users has increased. Human-centered design (HCD) provides a toolkit of research methods aimed at helping bridge the distance between technology design teams and end users. However, we have found that traditional approaches to HCD research methods are difficult to deploy in developing regions. In this paper, we share our experiences of adapting HCD research methodologies to the Central Asia context and some lessons we have learned. While our lessons are many, reconsidering the unit of analysis from the individual to larger social units was an early discovery that provided a frame for later research activities that focused on ubicomp development. We argue that lessons and challenges derived from our experience will generalize to other research investigations in which researchers are trying to adapt common HCD data collection methods to create ubiquitous technologies for and/or with distant audiences in developing regions.

As cloud computing's second wave begins to transform the networking industry, a snapshot of developments in software-defined networking standardization suggests how its components--devices, controllers, applications, service chains, network function virtualization, and interfaces--are maturing.

Welcome to the first issue of the updated IEEE Series on Network Testing and Analytics. The objective of this Series is to provide a forum across academia and the industry to address the application and development of a range of testing and analytics capabilities and practices that are required to model, measure, and evaluate the effectiveness of networks and systems over their life cycles. With the rapidly increasing scale and complexity of communications networks, the role of analytics- based network testing is expected to further increase in the future. The wealth of data available from networks can be used to better inform and direct testing to reduce costs, as well as to enable more effective optimization, management, and troubleshooting given the transition from intermittent testing toward constant, realtime monitoring.

The geographical scale of network testing depends on the size of the testbed. It could be as small as the desk area in a laboratory, medium on a campus or within a building, or as large as the wide area in the Internet. Traditionally, one would construct the testbed in a laboratory so that all the environmental parameters could be programmed and controlled, and the results could be reproduced. However, since some of the environmental parameters are too complicated to program and control, often we need to use the real environment as the testbed. This extends the testbed from a laboratory to a building, a campus, or even the Internet. As the parameters in the real environment are often not programmable and controllable, we thus lose the exact reproducibility of results. One common way to solve this problem is to repeat the experiments for a prolonged period and average over the huge number of repetitive runs. Then the testing period is usually weeks to months instead of hours. Another less common way is to "capture" the environmental parameters as traces and replay them onto a laboratory testbed. Precise reproducibility can be achieved, but the environment parameters in the captured traces can only be “replayed” instead of programmed and controlled. The results from such tracedriven testing are useful if the environments and captured traces are representative enough.

We present our experiences with an SMS-based system for providing transit information based solely on existing cellular and GPS networks. The aim is to permit the development of information services that do not rely on a central authority or complex web hosting. We developed and applied our system to the network of privately-run marshrutka buses in Bishkek, Kyrgyzstan. However, our goal is to more broadly address issues of ad-hoc shared transportation systems in the developing world. A custom designed GPS-GSM unit is placed on a vehicle, and users can query our server over SMS with their own non-GPS-enabled cell phones. We report on the accuracy of our location naming approach and estimates of bus arrival times. In addition, we summarize interviews with bus drivers and bus riders relating their views of the system and outline directions for future work. Our system is a grassroots solution to the persistent lack of transport information in developing countries.

In this paper, we describe several findings from a multi-year, multi-method study of how information and communication technologies have been adopted and adapted in Central Asia. We have found that mobile phone usage is outpacing the rate of Internet adoption, that access to the Internet is primarily through public access sites carrying with it issues regarding privacy and surveillance, that people rely on their social networks as information sources, that public institutions tend to be fairly weak as citizen resources, and that information seeking and communication are conflated in people's usage patterns with different technologies. In addition, in the developed world social networking software has grown rapidly and shown itself to have significant potential for mobilizing a population. Based on the collection of findings from Central Asia and observing patterns of technology usage in other parts of the world, our research leads to the conclusion that exploring mobile social software holds significant potential as an ICT that meshes well with preexisting patterns of communication and information seeking and also leverages the most predominant pattern of technology adoption. Many of the findings from this research echo results from studies in other geographic areas, and so we anticipate that much of this research will be relevant to developing regions generally.

This paper discusses how the importance of social networks for performing everyday tasks in the developing world leads to new considerations of the utility of social networking software (SNS). The paper presents some results from a multi-year, multi-method study in Central Asia that tracks patterns of technology adoption and adaptation, as well as shifts in media consumption and information seeking. Our results suggest SNS is a particularly compelling approach in resource-constrained environments (broadly defined) as a way to leverage and systematize the ad hoc processes people develop to navigate their everyday lives and information ecology.

Among the received eight submissions from the last call, we have accepted four of them, with one from academia, one from a national laboratory, one from industry, and one from a combined team of academia and industry. At the time of writing this editorial for these four articles, we have also finished the first-round review process of the next batch of nine submissions, and shall move to the second-round review process. Most accepted papers received the decision of major revision in the first-round review and needed to go through the second-round review. The number of submissions remains stable, and we should be able to pick at least one from product vendors, test laboratories, and test equipment vendors, which gives enough industrial flavor to this Series. The due dates remain June 1 and December 1 each year.

The articles in this special section focus on network testing technologies, applications, and services, including packet dispersion techniques and testing for future mobile networks.

The objective of the Network Testing Series of IEEE Communications Magazine is to provide a forum across academia and industry to address the design and implementation defects unveiled by network testing. In the industry, testing has been a mean to evaluate the design and implementation of a system. But in academia, a more common practice is to evaluate a design by mathematical analysis or simulation without actual implementations. A less common practice is to evaluate a design by testing a partial implementation. That is, academia focuses more deeply on algorithmic design evaluation, while industry has broader concerns on both algorithmic design and system implementation issues. Often an optimized algorithmic component cannot guarantee optimal operation of the whole system when other components throttle the overall performance.