We have developed a prototype teleoperated microsurgical robot (MSR-1) and associated virtual environment for eye surgery. Bidirectional pathways relay visual, auditory, and mechanical information between the MSR-1 master and slave. The surgeon wears a helmet (visual master) that is used to control the orientation of a stereo camera system (visual slave) observing the surgery. Images from the stereo camera system are relayed back to the helmet (or adjacent screen) where they are viewed by the surgeon. In each hand the surgeon holds a pseudotool (a shaft shaped like a microsurgical scalpel) that projects from the left and right limbs of a force reflecting interface (mechanical master). Movements of the left and right pseudotools cause corresponding movements (scaled down by 1 to 100 times) in the microsurgical tools held by the left and right limbs of the micromotion robot (mechanical slave) that performs the surgery. Forces exerted on the left and right limbs of the slave microsurgical robot via the microtools are reflected back (after being scaled up by 1 to 100 times) to the pseudotools and hence surgeon via actuators in the left and right limbs of the mechanical master. This system enables tissue cutting forces to be felt including those that would normally be imperceptible if they were transmitted directly to the surgeon's hands. The master and slave subsystems (visual, auditory, and mechanical) communicate through a computer system which serves to enhance and augment images, filter hand tremor, perform coordinate transformations, and perform safety checks. The computer system consists of master and slave computers that communicate via an optical fiber connection. As a result, the MSR-1 master and slave may be located at different sites, which permits remote robotic microsurgery to become a reality. MSR-1 is being used as an experimental testbed for studying the effects of feedforward and feedback delays on remote surgery and is used in research on enhancing the accuracy and dexterity of microsurgeons by creating mechanical and visual telepresence.

Phasor Measurement Units (PMUs) have enabled real-time power grid monitoring and control applications realizing an integrated power grid and communication system. The communication network formed by PMUs has strict latency requirements. If PMU measurements cannot reach the control centre within the latency bound, they will be invalid for calculation and may compromise the observability of the whole power grid as well as related applications. To address this issue, this study proposes a model to account for the power grid observability under communication constraints, where effective capacity is adopted to perform a cross-layer statistical analysis in the communication system. Based on this model, three algorithms are proposed for improving power grid observability, which are an observability redundancy algorithm, an observability sensitivity algorithm and an observability probability algorithm. These three algorithms aim at enhancing the power system observability via the optimal communication resource allocation for a given grid infrastructure. Case studies show that the proposed algorithms can improve the power system performance under constrained wireless communication resources. scalability [11]. Hence, wireless communication is playing a more and more important role in supporting the communication needs of modern grid [12]. In IEEE Standard 2030.2-2015 [13], the application of wireless technology for the communication between components within a transmission network and the operation control centre has been identified. There have been various researches addressing the wireless communication network in supporting communication between PMUs [14-17] as well as components of SCADA system [18-20]. Yet wireless communication is broadcasting in nature, which makes propagation signal prone to the influence of physical environment. The effect of channel fading will induce communication system performance fluctuation and then result in communication delay. However, the communication delay's influence on the power system observability performance as well as the inter-discipline study of the power system and communication system has not been well addressed, which is the major focus of this paper. Communication latency is a link layer metric used in the Open Systems Interconnection (OSI) model. In practical systems, communication delay has many sources. Some latencies are fixed or bounded, such as system overheads. Others are time-varying and hard, if not impossible, to be bound. One major uncertainty contributed to this time-varying latency is due to the communication channel fading effect. However, typically latency is a metric considered in link layer but not physical layer, where the latency study is further complicated when the channel has parameters that change with time. Therefore, it requires sophisticated cross-layer analysis to study such problems. Another challenge is that, in most fading channel scenarios, it is not feasible to provide a deterministic bound for the communication delay, which is a consequence ...

Just before the commercial roll-out of European 5G networks, 5G trials in realistic environments have been recently initiated all around Europe, as part of the Phase 3 projects of 5GPPP H2020 program [1]. The goal is to showcase 5G's capabilities and to convince stakeholders about its valueadding business potential. The approach is to offer advanced 5G connectivity to real vertical industries and showcase how it enables them to overcome existing 4G network limitation and other long-standing issues. The 5G EVE H2020 5GPPP project [2] offers cutting-edge 5G end-to-end facilities (in 4 countries) to diversified vertical industry experimenters. The objective is to understand the needs of prominent industries across Europe and to offer tailor-made 5G experience to each and every one of them. This paper contributes to the understanding of vertical services' needs, by offering a thorough and concise vertical requirements analysis methodology, including an examination of the 4G limitations. It also provides real-life values for the targeted KPIs of 3 vertical sectors namely Smart Industry (4.0), Smart Cities / Health and Smart Energy, while assisting market roll-out by prioritizing their connectivity needs.

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