In a stochastic game the play proceeds by steps from position to position, according to transition probabilities controlled jointly by the two players. We shall assume a finite number, N , of positions, and finite numbers m K , n K of choices at each position; nevertheless, the game may not be bounded in length. If, when at position k , the players choose their i th and j th alternatives, respectively, then with probability s i j k > 0 the game stops, while with probability p i j k l the game moves to position l . Define s = min k , i , j s i j k . Since s is positive, the game ends with probability 1 after a finite number of steps, because, for any number t , the probability that it has not stopped after t steps is not more than (1 − s ) t . 

Payments accumulate throughout the course of play: the first player takes a i j k from the second whenever the pair i , j is chosen at position k. If we define the bound M: M = max k , i , j | a i j k | , then we see that the expected total gain or loss is bounded by M + ( 1 − s ) M + ( 1 − s ) 2 M + … = M / s . (1)

The process therefore depends on N 2 + N matrices P K l = ( p i j k l | i = 1 , 2 , … , m K ; j = 1 , 2 , … , n K ) A K = ( a i j k | …

https://www.pnas.org/content/pnas/39/10/1095.full.pdf

Stochastic Games

With the widespread adoption of the Internet of Things (IoT), the number of connected devices is growing at an exponential rate, which is contributing to ever-increasing, massive data volumes. Real-time analytics on the massive IoT data, referred to as the “real-time IoT analytics” in this paper, is becoming the mainstream with an aim to provide an immediate or non-immediate actionable insights and business intelligence. However, the analytics network of the existing IoT systems does not adequately consider the requirements of the real-time IoT analytics. In fact, most researchers overlooked an appropriate design of the IoT analytics network while focusing much on the sensing and delivery networks of the IoT system. Since much of the IoT analytics network has often been taken as granted, the survey, in this paper, we aim to review the state-of-the-art of the analytics network methodologies, which are suitable for real-time IoT analytics. In this vein, we first describe the basics of the real-time IoT analytics, use cases, and software platforms, and then explain the shortcomings of the network methodologies to support them. To address those shortcomings, we then discuss the relevant network methodologies which may support the real-time IoT analytics. Also, we present a number of prospective research problems and future research directions focusing on the network methodologies for the real-time IoT analytics.

A Survey on Network Methodologies for Real-Time Analytics of Massive IoT Data and Open Research Issues

The emerging software defined networking (SDN) paradigm separates the data plane from the control plane and centralizes network control in an SDN controller. Applications interact with controllers to implement network services, such as network transport with quality of service. SDN facilitates the virtualization of network functions so that multiple virtual networks can operate over a given installed physical network infrastructure. Due to the specific characteristics of optical (photonic) communication components and the high optical transmission capacities, SDN-based optical networking poses particular challenges, but holds also great potential. In this article, we comprehensively survey studies that examine the SDN paradigm in optical networks; in brief, we survey the area of software defined optical networks (SDONs). We mainly organize the SDON studies into studies focused on the infrastructure layer, the control layer, and the application layer. Moreover, we cover SDON studies focused on network virtualization, as well as SDON studies focused on the orchestration of multilayer and multidomain networking. Based on the survey, we identify open challenges for SDONs and outline future directions.

pdf/software-defined-optical-networks-sdons-a-comprehensive-5d4vdijy6b.pdf

Software Defined Optical Networks (SDONs): A Comprehensive Survey

Software-Defined Networking

The exponential traffic growth, demand for high speed wireless data communications, as well as incessant deployment of innovative wireless technologies, services, and applications, have put considerable pressure on the mobile network operators (MNOs). Consequently, cellular access network performance in terms of capacity, quality of service, and network coverage needs further considerations. In order to address the challenges, MNOs, as well as equipment vendors, have given significant attention to the small-cell schemes based on cloud radio access network (C-RAN). This is due to its beneficial features in terms of performance optimization, cost-effectiveness, easier infrastructure deployment, and network management. Nevertheless, the C-RAN architecture imposes stringent requirements on the fronthaul link for seamless connectivity. Digital radio over fiber-based common public radio interface (CPRI) is the fundamental means of distributing baseband samples in the C-RAN fronthaul. However, optical links which are based on CPRI have bandwidth and flexibility limitations. Therefore, these limitations might constrain or make them impractical for the next generation mobile systems which are envisaged not only to support carrier aggregation and multi-band but also envisioned to integrate technologies like millimeter-wave (mm-wave) and massive multiple-input multiple-output antennas into the base stations. In this paper, we present comprehensive tutorial on technologies, requirements, architectures, challenges, and proffer potential solutions on means of achieving an efficient C-RAN optical fronthaul for the next-generation network such as the fifth generation network and beyond. A number of viable fronthauling technologies such as mm-wave and wireless fidelity are considered and this paper mainly focuses on optical technologies such as optical fiber and free-space optical. We also present feasible means of reducing the system complexity, cost, bandwidth requirement, and latency in the fronthaul. Furthermore, means of achieving the goal of green communication networks through reduction in the power consumption by the system are considered.

Toward an Efficient C-RAN Optical Fronthaul for the Future Networks: A Tutorial on Technologies, Requirements, Challenges, and Solutions

Data center and cloud architectures continue to evolve to address the needs of large-scale multi-tenant data centers and clouds. These needs are centered around seven dimensions: scalability in computing, storage, and bandwidth, scalability in network services, efficiency in resource utilization, agility in service creation, cost efficiency, service reliability, and security. This article focuses on the first five dimensions as they pertain to networking. Large data centers are targeting support for tens of thousands of servers, exabytes of storage, terabits per second of traffic, and tens of thousands of tenants. In a data center, server and storage resources are interconnected with packet switches and routers that provide for the bandwidth and multi-tenant virtual networking needs. Data centers are interconnected across the wide area network via routing and transport technologies to provide a pool of resources, known as the cloud. High-speed optical interfaces and dense wavelength-division multiplexing optical transport are used to provide for high-capacity transport intra- and inter-datacenter. This article reviews various switching, routing, and optical transport technologies, and their applicability in addressing the networking needs of large-scale multi-tenant data centers.

Technologies and protocols for data center and cloud networking

An approach is provided for determining a cloud provider identifier associated with a request to provision one or more communication services. The approach further involves validating the request by matching the cloud provider identifier against another copy of the cloud provider identifier associated with a session over which the provisioning request was received.

Method and apparatus for dynamic provisioning of communication services

A device may assign a virtual local area network (VLAN) to one or more specific links in a link aggregation group (LAG), and send traffic from the VLAN on the assigned one or more specific LAG links. Traffic from the same VLAN may be sent on one link in the LAG by selecting a hashing criterion or by pinning the VLAN to a primary link in the LAG and another link for redundancy purposes.

Pinning and protection on link aggregation groups

A collapsed or compact mobile architecture system includes connection nodes each comprising an access interface and at least one network interface; a backhaul network coupled to each of the connection nodes; and a mobility control unit coupled to the backhaul network. The mobility control unit comprises an Internet Protocol (IP) address server. Each of the connection nodes is configured to receive attachment requests from at least one user device. The mobility control unit is configured to receive first control plane signals from the connection nodes based on the attachment requests and transmit second control plane signals to the connection nodes based on the attachment requests. The mobility control unit is further configured to assign an IP address to each of the at least one user devices, based on the receive first control plane signals.

Collapsed mobile architecture

A device may receive a bandwidth (B) available on each link of a link aggregation group (LAG) that includes a number (N) of links, assign a primary LAG link and a redundant LAG link to a virtual local area network (VLAN), set an available bandwidth for primary link booking to (B-B/N), and set an available bandwidth for redundant link booking to (B/N).

Bandwidth admission control on link aggregation groups

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