These are just some of the headline-grabbing technologies that could be part of our lives once fifth-generation, or 5G, mobile networks roll out, telcos say. A pilot network in the one-north district is in the pipeline, announced jointly by Singtel and Ericsson in July. M1 will start South-east Asia field trials, and StarHub plans to switch on 5G base stations, both by year-end. But experts and industry players acknowledge that there may be a long road to 5G coverage in Singapore, not least because the dots that are to be connected aren't all in place yet. While the propounded benefits of 5G include higher data volumes and speeds, some raise eyebrows at holding trials and building infrastructure for a system not yet in place.

One lucrative new market that can be accessed through more innovative use of software is Industrial IoT (IIoT). For example, Statista recently found discrete manufacturing, transportation/ logistics, and utilities industries are projected to spend $40 billion each on IoT platforms, systems, and services by 2020. There are many software technologies that promise to revolutionize networks, including network slicing, ONAP and software-based architecture. However, it is that AI offers a transformative opportunity through its ability to industrialise large scale pattern recognition and automate complex processes. AI-augmented core and Radio Access Networks (RANs), for example, are set to offer carriers an unprecedented level of control and flexibility to develop higher performance services, providing a clear route to access mission critical applications such as IIoT, automotive and healthcare.

Shared edge computing platforms deployed at the radio access network are expected to significantly improve quality of service delivered by Application Service Providers (ASPs) in a flexible and economic way. However, placing edge service in every possible edge site by an ASP is practically infeasible due to the ASP's prohibitive budget requirement. In this paper, we investigate the edge service placement problem of an ASP under a limited budget, where the ASP dynamically rents computing/storage resources in edge sites to host its applications in close proximity to end users. Since the benefit of placing edge service in a specific site is usually unknown to the ASP a priori, optimal placement decisions must be made while learning this benefit. We pose this problem as a novel combinatorial contextual bandit learning problem. It is "combinatorial" because only a limited number of edge sites can be rented to provide the edge service given the ASP's budget. It is "contextual" because we utilize user context information to enable finer-grained learning and decision making. To solve this problem and optimize the edge computing performance, we propose SEEN, a Spatial-temporal Edge sErvice placemeNt algorithm. Furthermore, SEEN is extended to scenarios with overlapping service coverage by incorporating a disjunctively constrained knapsack problem. In both cases, we prove that our algorithm achieves a sublinear regret bound when it is compared to an oracle algorithm that knows the exact benefit information. Simulations are carried out on a real-world dataset, whose results show that SEEN significantly outperforms benchmark solutions. Mobile cloud computing (MCC) supports mobile applications in resource-constrained mobile devices by offloading computation-demanding tasks to the resource-rich remote cloud. L. Chen and J. Xu are with Department of Electrical and Computer Engineering, University of Miami, USA. S. Ren is with Department of Electrical and Computer Engineering, University of California, Riverside, USA.

O2, the phone network, has broken across the UK. The carrier has been hit by a major outage, according to the monitoring site Down Detector. It is also affecting other companies that uses O2's network, such as Giffgaff. Problems include failure to access data, make or receive calls or send text messages, according to users on Twitter. But it does not appear to be affecting all O2 users, and it is not clear how some people are still able to use their phones.

Toyota and Softbank have established a joint venture that could offer various autonomous vehicle services in the future. Softbank already has several self-driving partnerships with other companies. But this one called MONET (a portmanteau for "mobility network") will combine the powers of Toyota's Mobility Services Platform, which serves as its information infrastructure for connected vehicles, and of SoftBank's Internet of Things platform. Well, for the first phase of the partnership, they're planning to roll out a "just-in-time" vehicle dispatch service for companies and public agencies in Japan. However, MONET's ultimate goal is to roll out Autono-MaaS (autonomous mobility as a service) businesses using Toyota's e-Palette electric vehicle, which is still just a concept.

Titled "New Digital Horizons: Connect, Create, Innovate", the second edition of the event is being jointly organised by Cellular Operators Association of India (COAI), the Department of Telecommunications (DoT) and other government departments. The aim behind IMC2018 is building ideas, sharing knowledge and best practices, forming lasting industry relationships, fostering commercial opportunities, showcasing game changing mobile technology and product trends, providing sectoral insights, industrial solutions, case studies and workshops. The biggest ICTevent in South Asia, comprising of conclave and exhibition will include ministerial and partner programs in Digital India, Smart City, emerging technologies, Make in India projects, skill harmonisation, business innovation and knowledge sharing etc. There will be a technology showcase offering a glimpse into virtual reality, connected cars, m-health, smart wearables, smart home, artificial intelligence, drones, robotics, smart energy, internet of things, block chain, bitcoin, Machine Vision, Cloud Computing Holography, among others. The three day event will cover a wide array of topics, including but not confined to emerging technologies to new digital ecosystems, m-education, digital marketing to e-health, 5G and retail.

Over the last years, the computational power of mobile devices such as smartphones and tablets has grown dramatically, reaching the level of desktop computers available not long ago. While standard smartphone apps are no longer a problem for them, there is still a group of tasks that can easily challenge even high-end devices, namely running artificial intelligence algorithms. In this paper, we present a study of the current state of deep learning in the Android ecosystem and describe available frameworks, programming models and the limitations of running AI on smartphones. We give an overview of the hardware acceleration resources available on four main mobile chipset platforms: Qualcomm, HiSilicon, MediaTek and Samsung. Additionally, we present the real-world performance results of different mobile SoCs collected with AI Benchmark that are covering all main existing hardware configurations.

The challenges that operators face when trying to densify their outdoor networks are well documented. It is tough to gain access to the right sites without a time-consuming process of individually negotiating for each one, but even the best efforts to achieve a standardized template – let alone a common scale of pricing – have run into many problems (see separate item). The latest opposition from US cities to proposals by the FCC shows the significance of the problem – and the USA has progressed a lot further than most countries in seeking to address the issue, as its operators gear up for major densification programs, which will only intensify with 5G.

Future cellular Internet of Things (IoT) networks are going to be expected to deliver much lower latency and significantly higher reliability. Getting to that point, however, must be a step-by-step approach, said a telco equipment executive at Mobile World Congress Americas earlier this month. "Doing one at a time is not so difficult, but doing both at the same time is a challenge," said Jawad Manssour, head of Networks Portfolio Management at Product Area Networks with equipment maker Ericsson, during a presentation at the conference. Ericsson is one of the world's big three principal base station and cellular equipment vendors, along with Huawei and Nokia. Mobile network provider Sprint and Ericsson recently announced that they are building a distributed virtualized core IoT network and an IoT operating system. Manssour said one needs to look at IoT evolution in four distinct genres -- Massive IoT, High-Performance IoT, Critical IoT, and Industrial IoT -- to fully appreciate the challenges of IoT overall as use ramps up.

Software defined networking (SDN) represents a promising networking architecture that combines central management and network programmability. SDN separates the control plane from the data plane and moves the network management to a central point, called the controller, that can be programmed and used as the brain of the network. Recently, the research community has showed an increased tendency to benefit from the recent advancements in the artificial intelligence (AI) field to provide learning abilities and better decision making in SDN. In this study, we provide a detailed overview of the recent efforts to include AI in SDN. Our study showed that the research efforts focused on three main sub-fields of AI namely: machine learning, meta-heuristics and fuzzy inference systems. Accordingly, in this work we investigate their different application areas and potential use, as well as the improvements achieved by including AI-based techniques in the SDN paradigm.