The geopolitical hijacking of open networking: the case of Open RAN

This article investigates how discourses on open networking technologies provide a social imaginary that industry and government actors mobilize in an attempt to expand their control over mobile telecommunications networks. The case of recent initiatives aiming to ‘open up’ radio access network (or RAN, a key component of telecommunications infrastructure) with an ‘open RAN’ model reveals how the US Government came to promote this nascent technology to create an opposition between its own ‘open’ telecommunications networks versus proprietary and presumed ‘untrustworthy’ networks based on foreign equipment, namely Huawei. While a closer look casts doubts on the benefits of open radio access network to increase network security or to open up the equipment market, this case reveals how openness is an ambiguous notion that can be used by governments to exclude foreign trade enemies, while advocating for trust in telecommunications networks

Broadband Architectures, ISP Business Plans, and Open Access

Something suspiciously resembling a double standard exists in US regulation of broadband access carriers. Incumbent local exchange carriers?ILECs?are required to open their networks to competing service providers, while cable television companies are not. Where did Congress and the FCC get it right? In the telco case, where open access is required, and there is a nascent competitive market for telephony and DSL services, or in the case of cable data networks, where consumers usually have no choice but to buy their service from the cable company's affiliated ISP? Or is disparity the best policy

Orchestrating Service Migration for Low Power MEC-Enabled IoT Devices

Multi-Access Edge Computing (MEC) is a key enabling technology for Fifth Generation (5G) mobile networks. MEC facilitates distributed cloud computing capabilities and information technology service environment for applications and services at the edges of mobile networks. This architectural modification serves to reduce congestion, latency, and improve the performance of such edge colocated applications and devices. In this paper, we demonstrate how reactive service migration can be orchestrated for low-power MEC-enabled Internet of Things (IoT) devices. Here, we use open-source Kubernetes as container orchestration system. Our demo is based on traditional client-server system from user equipment (UE) over Long Term Evolution (LTE) to the MEC server. As the use case scenario, we post-process live video received over web real-time communication (WebRTC). Next, we integrate orchestration by Kubernetes with S1 handovers, demonstrating MEC-based software defined network (SDN). Now, edge applications may reactively follow the UE within the radio access network (RAN), expediting low-latency. The collected data is used to analyze the benefits of the low-power MEC-enabled IoT device scheme, in which end-to-end (E2E) latency and power requirements of the UE are improved. We further discuss the challenges of implementing such schemes and future research directions therein

Optical access networks: business guidelines and policy recommendations

Within the European FP7 project OASE, we have studied different business models for optical access networks. Based on an exploration of existing FTTH cases in Sweden, the Netherland and Germany, we developed a model for a cost-benefit analysis for the physical infrastructure provider (PIP) as well as the network provider (NP). Our evaluations have shown that the business case for the PIP is very difficult, even impossible in sparsely populated areas. Demand aggregation is an effective measure to guarantee earlier return on investment for the PIP. In-house deployment and CPE are significant cost factors for the NP. Business models that allow to allocate these costs to house or home owners should get enough attention. Furthermore, open access on fiber, wavelength and bit stream level allows for additional competition but also leads to additional opportunities and costs. Finally, some cross-sectorial effects can be expected from a fiber deployment. This could be an additional stimulus for national, regional or municipal governments to invest. In this way public support may be desirable

Modeling and Analysis of K-Tier Downlink Heterogeneous Cellular Networks

Cellular networks are in a major transition from a carefully planned set of large tower-mounted base-stations (BSs) to an irregular deployment of heterogeneous infrastructure elements that often additionally includes micro, pico, and femtocells, as well as distributed antennas. In this paper, we develop a tractable, flexible, and accurate model for a downlink heterogeneous cellular network (HCN) consisting of K tiers of randomly located BSs, where each tier may differ in terms of average transmit power, supported data rate and BS density. Assuming a mobile user connects to the strongest candidate BS, the resulting Signal-to-Interference-plus-Noise-Ratio (SINR) is greater than 1 when in coverage, Rayleigh fading, we derive an expression for the probability of coverage (equivalently outage) over the entire network under both open and closed access, which assumes a strikingly simple closed-form in the high SINR regime and is accurate down to -4 dB even under weaker assumptions. For external validation, we compare against an actual LTE network (for tier 1) with the other K-1 tiers being modeled as independent Poisson Point Processes. In this case as well, our model is accurate to within 1-2 dB. We also derive the average rate achieved by a randomly located mobile and the average load on each tier of BSs. One interesting observation for interference-limited open access networks is that at a given SINR, adding more tiers and/or BSs neither increases nor decreases the probability of coverage or outage when all the tiers have the same target-SINR.Comment: IEEE Journal on Selected Areas in Communications, vol. 30, no. 3, pp. 550 - 560, Apr. 201

Gumsense - a high power low power sensor node

The development of increasingly complex algorithms for sensor networks has made it difficult for researchers to implement their design on typical sensor network hardware with limited computing resources. The demands on hardware can also mean that small microcontrollers are not the ideal platform for testing computationally and/or memory intensive algorithms. Researchers would also like access to high level programming languages and a wider range of open source libraries. To address this problem we have designed and implemented an architecture, Gumsense which combines a low power micro-controller (8MHz MSP430) with a powerful processor (100-600MHz ARM) on a Gumstix board running Linux. This Open Embedded OS supports a wide variety of programming languages, package management and development tools. A similar hybrid approach was also used in the LEAP platform. The microcontroller wakes up frequently to manage tasks such as activating sensors and gathering data. The intended use-case is to power-up the ARM board and storage only during the brief periods it is needed, for example performing computation or communication

Computer Aided Verification

This open access two-volume set LNCS 13371 and 13372 constitutes the refereed proceedings of the 34rd International Conference on Computer Aided Verification, CAV 2022, which was held in Haifa, Israel, in August 2022. The 40 full papers presented together with 9 tool papers and 2 case studies were carefully reviewed and selected from 209 submissions. The papers were organized in the following topical sections: Part I: Invited papers; formal methods for probabilistic programs; formal methods for neural networks; software Verification and model checking; hyperproperties and security; formal methods for hardware, cyber-physical, and hybrid systems. Part II: Probabilistic techniques; automata and logic; deductive verification and decision procedures; machine learning; synthesis and concurrency. This is an open access book

Computer Aided Verification

This open access two-volume set LNCS 13371 and 13372 constitutes the refereed proceedings of the 34rd International Conference on Computer Aided Verification, CAV 2022, which was held in Haifa, Israel, in August 2022. The 40 full papers presented together with 9 tool papers and 2 case studies were carefully reviewed and selected from 209 submissions. The papers were organized in the following topical sections: Part I: Invited papers; formal methods for probabilistic programs; formal methods for neural networks; software Verification and model checking; hyperproperties and security; formal methods for hardware, cyber-physical, and hybrid systems. Part II: Probabilistic techniques; automata and logic; deductive verification and decision procedures; machine learning; synthesis and concurrency. This is an open access book

Finding novel relationships with integrated gene-gene association network analysis of Synechocystis sp. PCC 6803 using species-independent text-mining

The increasing move towards open access full-text scientific literature enhances our ability to utilize advanced text-mining methods to construct information-rich networks that no human will be able to grasp simply from 'reading the literature'. The utility of text-mining for well-studied species is obvious though the utility for less studied species, or those with no prior track-record at all, is not clear. Here we present a concept for how advanced text-mining can be used to create information-rich networks even for less well studied species and apply it to generate an open-access gene-gene association network resource for Synechocystis sp. PCC 6803, a representative model organism for cyanobacteria and first case-study for the methodology. By merging the text-mining network with networks generated from species-specific experimental data, network integration was used to enhance the accuracy of predicting novel interactions that are biologically relevant. A rule-based algorithm was constructed in order to automate the search for novel candidate genes with a high degree of likely association to known target genes by (1) ignoring established relationships from the existing literature, as they are already 'known', and (2) demanding multiple independent evidences for every novel and potentially relevant relationship. Using selected case studies, we demonstrate the utility of the network resource and rule-based algorithm to (i) discover novel candidate associations between different genes or proteins in the network, and (ii) rapidly evaluate the potential role of any one particular gene or protein. The full network is provided as an open source resource