Hierarchical Service Placement for Demanding Applications

The increasing scale of cloud environments requires more scalable orchestration systems for determining which physical resources are responsible for processing service requests. A centralised service placement lacks scalability while a fully decentralised approach only has a limited view of the system. For these reasons, this paper investigates a hierarchical approach for service placement in a distributed environment, which increases scalability while maintains high service placement quality. First, we design a polynomial optimisation algorithm to place services in cloud data centers based on our novel utility function. Then, we describe a hierarchical model with the need to only know a small subset of the data required by the global optimisation formulation. Simulations show that our approach is scalable and performs well, close to the centralised model

On the Feasibility of Using Current Data Centre Infrastructure for Latency-sensitive Applications

IEEE It has been claimed that the deployment of fog and edge computing infrastructure is a necessity to make high-performance cloud-based applications a possibility. However, there are a large number of middle-ground latency-sensitive applications such as online gaming, interactive photo editing and multimedia conferencing that require servers deployed closer to users than in globally centralised clouds but do not necessarily need the extreme low-latency provided by a new infrastructure of micro data centres located at the network edge, e.g. in base stations and ISP Points of Presence. In this paper we analyse a snapshot of today & #x0027;s data centres and the distribution of users around the globe and conclude that existing infrastructure provides a sufficiently distributed platform for middle-ground applications requiring a response time of $20-200\;ms$ . However, while placement and selection of edge servers for extreme low-latency applications is a relatively straightforward matter of choosing the closest, providing a high quality of experience for middle-ground latency applications that use the more widespread distribution of today & #x0027;s data centres, as we advocate in this paper, raises new management challenges to develop algorithms for optimising the placement of and the per-request selection between replicated service instances

UCIP: User controlled internet protocol

Internet protocols have developed significantly over the last 50 years but have reached a point where the further improvements in performance, resilience, security and privacy cannot be achieved by simple incremental changes. This paper proposes a new IP protocol that puts the user's end host at the centre of major algorithmic decisions. It consist of three new mechanisms: a private source routing establishment protocol that allows inter-domain traffic routes to be decided by the user and kept private from the providers whilst allowing for anonymous connections where two node can communicate without knowing the identity/address of the other end point; a mechanism to control reception of packets that mitigates denial-of-service attacks and a new directory system that puts the end user at the core of the decisions enabling anycast and mobility with a pub-sub mechanism with fine grain capabilities for describe resources. These changes allow end nodes to have a much tighter control of how they send and receive their traffic and provide a paradigm shift for the Internet ecosystem

R2L: Routing With Reinforcement Learning

In a packet network, the routes taken by traffic can be determined according to predefined objectives. Assuming that the network conditions remain static and the defined objectives do not change, mathematical tools such as linear programming could be used to solve this routing problem. However, networks can be dynamic or the routing requirements may change. In that context, Reinforcement Learning (RL), which can learn to adapt in dynamic conditions and offers flexibility of behavior through the reward function, presents as a suitable tool to find good routing strategies. In this work, we train an RL agent, which we call R2L, to address the routing problem. The policy function used in R2L is a neural network and we use an evolution strategy algorithm to determine its weights and biases. We tested R2L in two different scenarios: static and dynamic networks conditions. In the first, we used a 16-node network and experimented with different reward functions, observing that R2L was able to adapt its routing behavior accordingly. Finally, in the second experiment, we used a 5-node network topology where a given link's transmission rate changed during the simulation. In this scenario, we observed that R2L was able to deliver a competitive performance, compared to heuristic benchmarks, with changing network conditions

Indole: An evolutionarily conserved influencer of behavior across kingdoms

Indole is a key environmental cue that is used by many organisms. Based on its biochemistry, we suggest indole is used so universally, and by such different organisms, because it derives from the metabolism of tryptophan, a resource essential for many species yet rare in nature. These properties make it a valuable, environmental cue for resources almost universally important for promoting fitness. We then describe how indole is used to coordinate actions within organisms, to influence the behavior of conspecifics and can even be used to change the behavior of species that belong to other kingdoms. Drawing on the evolutionary framework that has been developed for understanding animal communication, we show how this is diversely achieved by indole acting as a cue, a manipulative signal, and an honest signal, as well as how indole can be used synergistically to amplify information conveyed by other molecules. Clarifying these distinct functions of indole identifies patterns that transcend different kingdoms of organisms

Quality of experience for 3-d immersive media streaming

Recent advances in media capture and processing technologies have enabled new forms of true 3-D media content that increase the degree of user immersion. The demand for more engaging forms of entertainment means that content distributors and broadcasters need to fine-tune their delivery mechanisms over the Internet as well as develop new models for quantifying and predicting user experience of these new forms of content. In the work described in this paper, we undertake one of the first studies into the quality of experience (QoE) of real-time 3-D media content streamed to virtual reality (VR) headsets for entertainment purposes, in the context of game spectating. Our focus is on tele-immersive media that embed real users within virtual environments of interactive games. A key feature of engaging and realistic experiences in full 3-D media environments, is allowing users unrestricted viewpoints. However, this comes at the cost of increased network bandwidth and the need of limiting network effects in order to transmit a realistic, real-time representation of the participants. The visual quality of 3-D media is affected by geometry and texture parameters while the temporal aspects of smooth movement and synchronization are affected by lag introduced by network transmission effects. In this paper, we investigate varying network conditions for a set of tele-immersive media sessions produced in a range of visual quality levels. Further, we investigate user navigation issues that inhibit free viewpoint VR spectating of live 3-D media. After reporting on a study with multiple users we analyze the results and assess the overall QoE with respect to a range of visual quality and latency parameters. We propose a neural network QoE prediction model for 3-D media, constructed from a combination of visual and network parameters

A System Architecture for Live Immersive 3D-Media Transcoding over 5G Networks

The upcoming 5G networks, among other technological advances, bring Network Function Virtualization (NFV) capabilities enabling deployment of application service intelligence on their Next Generation Core (NGC). Application specific logic is packaged into Virtual Network Functions (VNFs) so that their instantiation and deployment can be done at any node of the NGC, with their management and orchestration being maintained by the 5G infrastructure. While the number of instances of each VNF and their placement inside the NGC network are managed by the 5G infrastructure, such management cannot be optimal without application context. In this paper, we propose a 5G oriented system architecture for a next generation augmented virtuality tele-immersive two-player video game application. In the presented video game, the players compete in a capture the flag race in an innovative game movement control setting which uses motion capture technology to allow the players to interact with the game via their body posture and hand gestures. On the top of this, real-time 3D-Reconstruction technology is utilized to create 3D avatars of the players and embed them inside the game environment. Apart from the players, the application also supports real-time spectating of the game action by a considerable amount of spectators that join the live game via client software designed for desktop PCs, smartphones and tablets, connected through mobile or fixed access networks. To distribute the 3D traffic to such a number of consumers that have different device capabilities and are located at varying geographical locations while offering the highest possible Quality of Experience (QoE), is a challenging task. One of the contemporary ways to address this problem is via adaptive streaming. To realize this concept, realtime 3D-Media Transcoders need to be employed. The proposed system architecture considers packaging the aforementioned 3D-Media Transcoders as VNFs that can be deployed on 5G infrastructure. In the paper, it is shown that such an architecture can decrease costs for a given level of offered QoE, with evident benefits for the game service's shareholders. While the application type presented in this paper is fixed, the proposed system architecture can be adopted by other applications of similar context with similar benefits gained from the flexible deployment of virtualised applications in 5G networks

Captive-born collared peccary (Pecari tajacu, Tayassuidae) fails to discriminate between predator and non-predator models

Captive animals may lose the ability to recognize their natural predators, making conservation programs more susceptible to failure if such animals are released into the wild. Collared peccaries are American tayassuids that are vulnerable to local extinction in certain areas, and conservation programs are being conducted. Captive-born peccaries are intended for release into the wild in Minas Gerais state, southeastern Brazil. In this study, we tested the ability of two groups of captive-born collared peccaries to recognize their predators and if they were habituated to humans. Recognition tests were performed using models of predators (canids and felids) and non-predators animals, as well as control objects, such as a plastic chair; a human was also presented to the peccaries, and tested as a separate stimulus. Anti-predator defensive responses such as fleeing and threatening displayswere not observed in response to predator models. Predator detection behaviors both from visual and olfactory cues were displayed, although they were not specifically targeted at predator models. These results indicate that collared peccaries were unable to recognize model predators. Habituation effects, particularly on anti-predator behaviors, were observed both with a 1-h model presentation and across testing days. Behavioral responses to humans did not differ from those to other models. Thus, if these animals were to be released into the wild, they should undergo anti-predator training sessions to enhance their chances of survival

High Amplitude Phase Resetting in Rev-Erbα/Per1 Double Mutant Mice

Over time, organisms developed various strategies to adapt to their environment. Circadian clocks are thought to have evolved to adjust to the predictable rhythms of the light-dark cycle caused by the rotation of the Earth around its own axis. The rhythms these clocks generate persist even in the absence of environmental cues with a period of about 24 hours. To tick in time, they continuously synchronize themselves to the prevailing photoperiod by appropriate phase shifts. In this study, we disrupted two molecular components of the mammalian circadian oscillator, Rev-Erbα and Period1 (Per1). We found that mice lacking these genes displayed robust circadian rhythms with significantly shorter periods under constant darkness conditions. Strikingly, they showed high amplitude resetting in response to a brief light pulse at the end of their subjective night phase, which is rare in mammals. Surprisingly, Cry1, a clock component not inducible by light in mammals, became slightly inducible in these mice. Taken together, Rev-Erbα and Per1 may be part of a mechanism preventing drastic phase shifts in mammals