What Can Wireless Cellular Technologies Do about the Upcoming Smart Metering Traffic?

The introduction of smart electricity meters with cellular radio interface puts an additional load on the wireless cellular networks. Currently, these meters are designed for low duty cycle billing and occasional system check, which generates a low-rate sporadic traffic. As the number of distributed energy resources increases, the household power will become more variable and thus unpredictable from the viewpoint of the Distribution System Operator (DSO). It is therefore expected, in the near future, to have an increased number of Wide Area Measurement System (WAMS) devices with Phasor Measurement Unit (PMU)-like capabilities in the distribution grid, thus allowing the utilities to monitor the low voltage grid quality while providing information required for tighter grid control. From a communication standpoint, the traffic profile will change drastically towards higher data volumes and higher rates per device. In this paper, we characterize the current traffic generated by smart electricity meters and supplement it with the potential traffic requirements brought by introducing enhanced Smart Meters, i.e., meters with PMU-like capabilities. Our study shows how GSM/GPRS and LTE cellular system performance behaves with the current and next generation smart meters traffic, where it is clearly seen that the PMU data will seriously challenge these wireless systems. We conclude by highlighting the possible solutions for upgrading the cellular standards, in order to cope with the upcoming smart metering traffic.Comment: Submitted; change: corrected location of eSM box in Fig. 1; May 22, 2015: Major revision after review; v4: revised, accepted for publicatio

Iowa Communications Network Performance Report, FY2007

Agency Performance Repor

Internet Accounting

This article provides an introduction to Internet accounting and discusses the status of related work within the IETF and IRTF, as well as certain research projects. Internet accounting is different from accounting in POTS. To understand Internet accounting, it is important to answer questions like "what is being paid for" and "who is being paid". With respect to the question "what is being paid for" a distinction can be made between transport accounting and content accounting. Transport accounting is interesting since techniques like DiffServ enable the provision of different quality of service classes; each class will be charged differently to avoid all users selecting the same top-level class. The interest in content accounting finds its roots in the fast growth of commercial offerings over the Internet; examples of such offerings include remote video and software distribution. The question "who is being paid" has two possible answers: the network provider or the owner of the content. The case in which the network provider issues the bill is called provider-based accounting. Since this case will become more and more important, this article introduces a new architecture for provider-based accounting

Economic FAQs About the Internet

This is a set of Frequently Asked Questions (and answers) about the economic, institutional, and technological structure of the Internet. We describe the history and current state of the Internet, discuss some of the pressing economic and regulatory problems, and speculate about future developments.Internet, telecommunications, congestion pricing, National Information Infrastructure

Interactive Visual Analysis of Networked Systems: Workflows for Two Industrial Domains

We report on a first study of interactive visual analysis of networked systems. Working with ABB Corporate Research and Ericsson Research, we have created workflows which demonstrate the potential of visualization in the domains of industrial automation and telecommunications. By a workflow in this context, we mean a sequence of visualizations and the actions for generating them. Visualizations can be any images that represent properties of the data sets analyzed, and actions typically either change the selection of data visualized or change the visualization by choice of technique or change of parameters

S-FaaS: Trustworthy and Accountable Function-as-a-Service using Intel SGX

Function-as-a-Service (FaaS) is a recent and already very popular paradigm in cloud computing. The function provider need only specify the function to be run, usually in a high-level language like JavaScript, and the service provider orchestrates all the necessary infrastructure and software stacks. The function provider is only billed for the actual computational resources used by the function invocation. Compared to previous cloud paradigms, FaaS requires significantly more fine-grained resource measurement mechanisms, e.g. to measure compute time and memory usage of a single function invocation with sub-second accuracy. Thanks to the short duration and stateless nature of functions, and the availability of multiple open-source frameworks, FaaS enables non-traditional service providers e.g. individuals or data centers with spare capacity. However, this exacerbates the challenge of ensuring that resource consumption is measured accurately and reported reliably. It also raises the issues of ensuring computation is done correctly and minimizing the amount of information leaked to service providers. To address these challenges, we introduce S-FaaS, the first architecture and implementation of FaaS to provide strong security and accountability guarantees backed by Intel SGX. To match the dynamic event-driven nature of FaaS, our design introduces a new key distribution enclave and a novel transitive attestation protocol. A core contribution of S-FaaS is our set of resource measurement mechanisms that securely measure compute time inside an enclave, and actual memory allocations. We have integrated S-FaaS into the popular OpenWhisk FaaS framework. We evaluate the security of our architecture, the accuracy of our resource measurement mechanisms, and the performance of our implementation, showing that our resource measurement mechanisms add less than 6.3% latency on standardized benchmarks