Existing optical and wireless networks designed to support today's services may not be suitable for the emerging services, such as machine-to-machine applications of the Internet-of-Things paradigm and tactile-haptic applications of the Tactile Internet paradigm. Some of these applications must adhere to stringent quality of service requirements, especially an ultra-low end-to-end latency constraint of approximately 1 ms. In this paper, we investigate the feasibility of the wireless local area network (WLAN) infrastructure, specifically the IEEE 802.11 HCF Controlled Channel Access (HCCA) media access control (MAC) protocol, in supporting low-latency applications. The scenario considered is tactile-haptic data transmission between body-worn data collection devices and a wireless access point. In particular, we focus on uplink direction rather than downlink direction, because uplink data transmission forms a latency bottleneck of this particular network. In this paper, we first formulate an analytical model of the HCCA using a queuing theory to evaluate the average uplink latency. We then carry out global sensitivity analyses to understand the implications of various timing and network parameters on the uplink latency. Using these insights, we propose a novel strategic parameter selection (SPS) algorithm that effectively reduces uplink latency of the IEEE 802.11 WLAN. This paper provides insights into WLAN design such that latency-sensitive applications can be supported in the near future.

The Internet has evolved a long way from transporting basic web data to transporting traffic instigated by new emerging applications that are available today. One such application is remote human-to-machine interaction, in which touch and actuation related information is delivered over the network. These applications are extremely sensitive to latency, with some reporting latency requirements in the millisecond range. Therefore, it is crucial to minimize latency experienced in each and every segment of the network. In this paper, we consider a scenario in which tactile body-worn devices are connected using the IEEE 802.11 network, and analyze the wireless transmission latency from these devices to the wireless access point, when the hybrid coordination function controlled channel access (HCCA) MAC protocol is used. In particular, we use queuing theory based approach to derive closed-form expressions for the average latency. We use the insights gained from our latency analysis to propose a new service interval selection method that outperforms the HCCA reference design. We show for the first time the parameters that have significant impact on latency and how these can be manipulated to meet the stringent latency constraints.

Today, video-on-demand (VoD) systems are challenged by a growing number of users, growing sizes of libraries, and increasing video streaming rates. Therefore, scalability and the bandwidth efficiency of VoD systems have become important considerations. In this paper, we propose a scalable and bandwidth efficient delivery scheme for VoD systems, which optimally exploits the storage and multicast capabilities to reduce the consumption of server capacity resources. Our proposed scheme, which we call prepopulation assisted batching with multicast patching (PAB-MP), facilitates video multicast from the server by strategic preplacement of initial segments of videos at the end-users' devices. Using an analytical approach, we show how the parameters for the PAB-MP scheme can be selected to achieve optimal performance. Moreover, we propose methods to replicate and place the initial video segments (IVSs) across the end-users' devices such that load arising from IVSs is evenly distributed among user-nodes. Using simulations, we show that our proposed scheme effectively reduces the load on the server especially under high load, while imposing less burden on individual user nodes. Simulation results indicate that our proposed PAB-MP scheme is significantly more scalable than the other popular approaches that exploit multicast and storage.

Video on Demand (VoD) service has become an increasingly popular service in recent years as a result of the rapid deployment of Fiber-to-the-Home networks. Due to its enormous bandwidth and stringent quality of service requirements, deploying an efficient and scalable VoD service still remains a challenge. In this paper, we propose a peer-to peer (P2P) VoD distribution scheme for PONs in which the P2P delivery is localized to within the same access network and in which a selected set of movies is pre-fetched into the customer premises equipment during off-peak hours. The proposed delivery scheme mitigates the load from the VoD server by exploiting the participation of the customer equipment in VoD distribution. In turn, this optimizes bandwidth consumption of the VoD service in both core and metro networks as the P2P video traffic is localized within the access network. We formulate movie pre-fetching as an optimization problem which determines the number of copies of each movie to be pre-fetched, and we propose a heuristic algorithm to solve it. Using simulations we show that our proposed replication algorithm performs much better than existing popularity based replication algorithm that has been proposed for similar purposes. Moreover, we show that our proposed delivery scheme effectively reduced the server load in busy hours while having high but random server load reduction in off-peak hours of service.

We present energy consumption models of video-on-demand (VoD) services delivered through newly proposed localized hybrid peer-to-peer (P2P) and localized peer-assisted patching with multicast video delivery methods over optical access networks. In this paper, we demonstrate through simulations that the localized peer-assisted patching with multicast video delivery method consumes the lowest network transport energy for popular VoD channels while localized hybrid P2P method consumes the lowest network transport energy for less popular channels. Nevertheless, both schemes outperform the conventional server centric content distribution network in term of overall network energy consumption.

Video on Demand (VoD) service is regarded as one of the most promising services over increasingly deployed next generation broadband access networks. The distributed server architecture, in which the popular content is cached at a location closer to the viewer, is a widely used methodology to optimize the transport capacity of VoD delivery. However, due to the dynamic (change with time) nature of movie popularity distribution, identifying the popular content and updating the cache servers accordingly is not straightforward. In this paper, using a novel caching architecture for Passive Optical Networks (PON), we discuss the need for a fast caching algorithm that can respond to time changing movie popularity distribution, and we propose a novel Last-k caching algorithm, which identifies the popular content using the most recent statistics. The proposed algorithm estimates movie popularity using most recent inter-arrival times of movie requests and updates the cache accordingly such that the most popular content at any given time would reside in the cache. Simulations indicate that the proposed algorithm out-performs existing algorithms by effectively responding to the dynamic nature of movie popularity distribution.