Distribution system provides a link between the high voltage transmission system and low voltage consumers thus I2R loss in a distributed system is high because of low voltage and high current. Distribution companies (DISCOs) have an economic enticement to reduce losses in their networks. Usually, this enticement is the cost difference between real and standard losses. Therefore, if real losses are higher than the standard ones, the DISCOs are economically penalized or if the opposite happens, they obtain a profit. Thus loss minimization problem is a well researched topic and all previous approaches vary from each other by selection of tool for loss minimization and thereafter either in their problem formulation or problem solution methods employed. Many methods of loss reduction exist like feeder reconfiguration, capacitor placement, high voltage distribution system, conductor grading, Distributed Generator (DG) Allocation etc. This paper gives a bibliographical survey, general background and comparative analysis of three most commonly used techniques (i) Capacitor Placement, (ii) Feeder Reconfiguration, (iii) and DG Allocation for loss minimization in distribution network based on over 147 published articles, so that new researchers can easily find literature particularly in this area.

Loss minimization techniques used in distribution network: bibliographical survey

Quality of Service-enabled applications and services rely on Traffic Engineering-based (TE) Label Switched Paths (LSP) established in core networks and controlled by the GMPLS control plane. Path computation process is crucial to achieve the desired TE objective. Its actual effectiveness depends on a number of factors. Mechanisms utilized to update topology and TE information, as well as the latency between path computation and resource reservation, which is typically distributed, may affect path computation efficiency. Moreover, TE visibility is limited in many network scenarios, such as multi-layer, multi-domain and multi-carrier networks, and it may negatively impact resource utilization. The Internet Engineering Task Force (IETF) has promoted the Path Computation Element (PCE) architecture, proposing a dedicated network entity devoted to path computation process. The PCE represents a flexible instrument to overcome visibility and distributed provisioning inefficiencies. Communications between path computation clients (PCC) and PCEs, realized through the PCE Protocol (PCEP), also enable inter-PCE communications offering an attractive way to perform TE-based path computation among cooperating PCEs in multi-layer/domain scenarios, while preserving scalability and confidentiality. This survey presents the state-of-the-art on the PCE architecture for GMPLS-controlled networks carried out by research and standardization community. In this work, packet (i.e., MPLS-TE and MPLS-TP) and wavelength/spectrum (i.e., WSON and SSON) switching capabilities are the considered technological platforms, in which the PCE is shown to achieve a number of evident benefits.

/pdf/a-survey-on-the-path-computation-element-pce-architecture-17m6xw5gna.pdf

A Survey on the Path Computation Element (PCE) Architecture

With the rapid increase in demand for mobile data, mobile network operators are trying to expand wireless network capacity by deploying wireless local area network (LAN) hotspots on to which they can offload their mobile traffic. However, these network-centric methods usually do not fulfill the interests of mobile users (MUs). Taking into consideration many issues such as different applications' deadlines, monetary cost and energy consumption, how the MU decides whether to offload their traffic to a complementary wireless LAN is an important issue. Previous studies assume the MU's mobility pattern is known in advance, which is not always true. In this paper, we study the MU's policy to minimize his monetary cost and energy consumption without known MU mobility pattern. We propose to use a kind of reinforcement learning technique called deep Q-network (DQN) for MU to learn the optimal offloading policy from past experiences. In the proposed DQN based offloading algorithm, MU's mobility pattern is no longer needed. Furthermore, MU's state of remaining data is directly fed into the convolution neural network in DQN without discretization. Therefore, not only does the discretization error present in previous work disappear, but also it makes the proposed algorithm has the ability to generalize the past experiences, which is especially effective when the number of states is large. Extensive simulations are conducted to validate our proposed offloading algorithms.

A deep reinforcement learning based approach for cost- and energy-aware multi-flow mobile data offloading

Use of disaggregated equipment in optical transport networks is emerging as an attractive solution to bring flexibility and break vendor lock-in dependencies. The disaggregation process requires standard protocols and interfaces between the control plane and network equipment. NETCONF has been selected as the standard protocol, and multiple initiatives are currently working on the definition of standard models for each type of data plane device. Different levels of disaggregation of the data plane are under evaluation, and it is still not clear up to which level it will be useful to disaggregate the data plane. The disaggregation of optical networks yielded the development of several controllers based on software-defined networking concepts, providing an environment for creating and deploying networking application on optical networks. Among them, the Open Network Operating System (ONOS) controller features the most active community with the recent establishment of the Open and Disaggregated Transport Network (ODTN) working group, specifically focused on the introduction of required functionality to control and monitor disaggregated transport networks. This paper reports on the state-of-the-art, potentials, and limitations of the ONOS controller applied to disaggregated optical networks with specific focus on the ongoing activities within the ODTN working group. Then, the paper describes a set of experiments performed on a setup including both emulated and real optical devices controlled with ONOS. The performed experiments consider both the establishment of a connectivity service and the recovery of the connectivity in case of failure on the data plane.

Control of open and disaggregated transport networks using the Open Network Operating System (ONOS) [Invited]

With offloading the tasks that mobile users (MUs) running in their mobile devices (MDs) to the data centers of remote public clouds, mobile cloud computing (MCC) can greatly improve the computing capacity and prolong the battery life of MDs. However, the data centers of remote public cloud are generally far from the MUs, thus long delay will be caused due to the transmission from the base station to the public clouds over the Internet. Mobile edge computing (MEC) is recognized as a promising technique to augment the computation capabilities of MDs and shorten the transmission delay. Nevertheless, compared with the traditional MCC and MEC generally has a limited number of cloud resources. Therefore, making a choice on offloading task to the MCC or MEC is a challenging issue for each MU. In this paper, we investigate service selection in a mobile cloud architecture, in which MUs select cloud services from two cloud service providers (CSPs), i.e., public cloud service provider (PSP) and an edge cloud service provider (ESP). We use M/M/$\infty $ queue and M/M/1 queue to model PSP and ESP, respectively. We analyze the interaction of the two CSPs and MUs by adopting Stackelberg game, in which PSP and ESP set the prices first, and then the MUs decide to select cloud services based on performances and prices. In particular, we study the relationship between PSP and ESP in the simultaneous-play game (SPG) scenario, in which they compete to set prices of their cloud services simultaneously. Our numerical results show that MUs prefer to select service from the edge cloud if the number of tasks they run is small. In another hand, more tasks will be offloaded to the remote public cloud if the number of tasks they run becomes large.

/pdf/optimal-pricing-and-service-selection-in-the-mobile-cloud-5e34jbwbvn.pdf

Optimal Pricing and Service Selection in the Mobile Cloud Architectures

A dynamic and joint optimisation of computational and network resources may significantly improve the performance of grid-enabled applications. In this paper, the path computation element protocol (PCEP) is first proposed as standard grid network service interface between grid resource manager (GRM) and network resource manager (NRM). Then, two different schemes exploiting the PCEP protocol and the PCE capability to provide synchronised and optimal path computations are proposed. The schemes allow the GRM to exploit performance metrics representative of the expected network resource utilisation and to perform a jointly optimal choice of both computational and network resources. Simulation results show that the proposed schemes significantly improve the overall amount of successfully established grid services. Experimental implementations on the 'JGN2plus' testbed are presented to show that the proposed schemes avoid control plane extensions or interfaces specifically designed for grid purposes and do not substantially affect the overall grid service delivery time.

/pdf/optical-grid-networking-exploiting-path-computation-element-3o8ux2c2u7.pdf

Optical grid networking exploiting path computation element (PCE) architecture

A fast logical topology design with simulated annealing in IP over WDM networks

This paper proposes dynamic host-to-host wavelength path provisioning with distributed host network interface configuration. Path provisioning and host configuration are cooperated to enable automatic distributed communication setup. The implemented system is addressed with experiment result.

https://ieeexplore.ieee.org/iel5/4768555/4773348/04773370.pdf

Dynamic host-to-host wavelength path provisioning with distributed host network interface configuration

We demonstrate the emergent integration and control of surviving multi-vendor optical systems after huge-disasters. Interconnecting surviving multi-vendor networks is not only feasible but also the most cost-efficient approach to the quick disaster recovery.

Emergent Integration and Control of Multi-Vendor Optical Networks

Extending the researches on wavelength switched optical networks (WSON), efficient integration of the novel optical
packet switching network and wavelength switching-based optical circuit switching network technologies which offers
both best-effort packet delivery and QoS guaranteed lightpath services has been being studied. In addition, researches on
the optical-layer transparent data processing, such as all-optical wavelength multicasting, all-optical 3R regeneration, etc,
are conducted simultaneously. It is believed that future innovative optical network services (INSes) would be built on
these novel future-proof technologies, and foster colorful applications in the new generation networks. Before the wide
applications of INS in different fields, there would be a foreseeable strong requirement for INS firstly posed by pioneer
grid applications, e.g., e-science, e-government, and e-banking, etc, which would require the high-performance
underlying networks. Our research here is motivated to glue the optical networks and grid applications by integrating
lightpath, geographically distributed INS systems and grid resources (e.g., computers, storages, instruments, etc.), and
finally offering an easy-to-use high performance networked grid computing environment-optical grid network (OGN)
to user applications. In this paper, we introduce our research activities of a distributed optical grid network infrastructure
(OGNI), and the creation of the future easy-to-use INS based on OGNI. The proposals have been validated through fieldtrial
experiments over a developed WSON testbed.

Sugang Xu

Papers

Optical grid networking exploiting path computation element (PCE) architecture

A fast logical topology design with simulated annealing in IP over WDM networks

Dynamic host-to-host wavelength path provisioning with distributed host network interface configuration

Emergent Integration and Control of Multi-Vendor Optical Networks

A distributed optical grid network infrastructure for future easy-to-use innovative network services