Mohammed Samaka

A survey on service function chaining

Cloud computing is gaining significant attention and virtualized datacenters are becoming popular as a cost-effective infrastructure. The network services are transitioning from a host-centric to a data-centric model moving the data and the computational resources closer to the end users. To meet the dynamic user demands, network operators have chosen to use elastic virtual resources to implement network services over static rigid physical model. With the advent of network function virtualization (NFV), network services instances are provisioned across multiple clouds for performance and load balancing purposes. Interconnection of these instances to form a complete end-to-end network service is complex, time consuming and expensive task. Service function chaining (SFC) is a mechanism that allows various service functions to be connected to each to form a service enabling carriers to benefit from virtualized software defined infrastructure. SFC is an enabler for NFV, providing a flexible and economical alternative to todays static environment for Cloud Service providers (CSPs), Application Service Providers (ASPs) and Internet Service Providers (ISPs). This paper provides a closer look at the current SFC architecture and a survey of the recent developments in SFC including its relevance with NFV to help determine the future research directions and the standardization efforts of SFC. Finally, the paper discusses open research topics in relevance with the SFC architecture and demonstrates a need for an analytical model for the SFC architecture to achieve the optimal performance.

Application delivery in multi-cloud environments using software defined networking

Today, most large Application Service Providers (ASPs) such as Google, Microsoft, Yahoo, Amazon and Facebook operate multiple geographically distributed datacenters, serving a global user population that are often mobile. However, the service-centric deployment and delivery semantics of these modern Internet-scale applications do not fit naturally into the Internet’s host-centric design. In this service-centric model, users connect to a service, and not a particular host. A service virtualizes the application endpoint, and could be replicated, partitioned, distributed and composed over many different hosts in many different locations. To address this gap between design and use, ASPs deploy a service-centric network infrastructure within their enterprise datacenter environments while maintaining a (virtual) host-centric service access interface with the rest-of-the-Internet. This is done using data-plane mechanisms including data-plane proxying (virtualizing the service endpoint) and Layer 7 (L7) traffic steering (dynamically mapping service requests to different application servers and orchestrating service composition and chaining). However, deploying and managing a wide-area distributed infrastructure providing these service-centric mechanisms to support multi-data center environments is prohibitively expensive and difficult even for the largest of ASPs. Therefore, although recent advances in cloud computing make distributed computing resources easily available to smaller ASPs on a very flexible and dynamic pay-as-you-go resource-leasing model, it is difficult for these ASPs to leverage the opportunities provided by such multi-cloud environments without general architectural support for a service-centric Internet. In this paper, we present a new service-centric networking architecture for the current Internet called OpenADN. OpenADN will allow ASPs to be able to fully leverage multi-cloud environments for deploying and delivering their applications over a shared, service-centric, wide-area network infrastructure provided by third-party providers including Internet Service Providers (ISPs), Cloud Service Providers (CSPs) and Content Delivery Networks (CDNs). The OpenADN design leverages the recently proposed framework of Software Defined Networking (SDN) to implement and manage the deployment of OpenADN-aware devices. This paper focuses mostly on the data-plane design of OpenADN.

Multi-cloud Distribution of Virtual Functions and Dynamic Service Deployment: Open ADN Perspective

Network Function Virtualization (NFV) and Service Chaining (SC) are novel service deployment approaches in the contemporary cloud environments for increased flexibility and cost efficiency to the Application Service Providers and Network Providers. However, NFV and SC are still new and evolving topics. Optimized placement of these virtual functions is necessary for acceptable latency to the end-users. In this work we consider the problem of optimal Virtual Function (VF) placement in a multi-cloud environment to satisfy the client demands so that the total response time is minimized. In addition we consider the problem of dynamic service deployment for OpenADN, a novel multi-cloud application delivery platform.

Optimal virtual network function placement in multi-cloud service function chaining architecture

Service Function Chaining (SFC) is the problem of deploying various network service instances over geographically distributed data centers and providing inter-connectivity among them. The goal is to enable the network traffic to flow smoothly through the underlying network, resulting in an optimal quality of experience to the end-users. Proper chaining of network functions leads to optimal utilization of distributed resources. This has been a de-facto model in the telecom industry with network functions deployed over underlying hardware. Though this model has served the telecom industry well so far, it has been adapted mostly to suit the static behavior of network services and service demands due to the deployment of the services directly over physical resources. This results in network ossification with larger delays to the end-users, especially with the data-centric model in which the computational resources are moving closer to end users. A novel networking paradigm, Network Function Virtualization (NFV), meets the user demands dynamically and reduces operational expenses (OpEx) and capital expenditures (CapEx), by implementing network functions in the software layer known as virtual network functions (VNFs). VNFs are then interconnected to form a complete end-to-end service, also known as service function chains (SFCs). In this work, we study the problem of deploying service function chains over network function virtualized architecture. Specifically, we study virtual network function placement problem for the optimal SFC formation across geographically distributed clouds. We set up the problem of minimizing inter-cloud traffic and response time in a multi-cloud scenario as an ILP optimization problem, along with important constraints such as total deployment costs and service level agreements (SLAs). We consider link delays and computational delays in our model. The link queues are modeled as M/D/1 (single server/Poisson arrival/deterministic service times) and server queues as M/M/1 (single server/Poisson arrival/exponential service times) based on the statistical analysis. In addition, we present a novel affinity-based approach (ABA) to solve the problem for larger networks. We provide a performance comparison between the proposed heuristic and simple greedy approach (SGA) used in the state-of-the-art systems. Greedy approach has already been widely studied in the literature for the VM placement problem. Especially we compare our proposed heuristic with a greedy approach using first-fit decreasing (FFD) method. By observing the results, we conclude that the affinity-based approach for placing the service functions in the network produces better results compared against the simple greedy (FFD) approach in terms of both, total delays and total resource cost. We observe that with a little compromise (gap of less than 10% of the optimal) in the solution quality (total delays and cost), affinity-based heuristic can solve the larger problem more quickly than ILP.

Network Slicing for 5G: Challenges and Opportunities

Network slicing for 5G provides Network-as-a-Service (NaaS) for different use cases, allowing network operators to build multiple virtual networks on a shared infrastructure. With network slicing, service providers can deploy their applications and services flexibly and quickly to accommodate diverse services’ specific requirements. As an emerging technology with a number of advantages, network slicing has raised many issues for the industry and academia alike. Here, the authors discuss this technology’s background and propose a framework. They also discuss remaining challenges and future research directions.

Altmetrics for Country-Level Research Assessment

Changes are occurring in scholarly communication and the geography of science.Policymakersand research funding agencies are looking for ways to measure the comprehensive impact of research and benefit from the research experiences of other nations. Recently, altmetrics have been used to measure broader impact of research activities.In this paper, we study altmetrics based on the country-levelimpact andfind that altmetrics can support research evaluation for all countries studied. We compare altmetrics with several traditional metrics and findsignificant relationshipsbetween country-level altmetrics and the number of publications, citations, h-index, and gross domestic expenditure on research and development (GERD). We also find a significant yearly increase in the number of articles published between 2010 and 2014 that received altmetrics.

Multi-objective scheduling of micro-services for optimal service function chains

Lately application service providers (ASPs) and Internet service providers (ISPs) are being confronted with the unprecedented challenge of accommodating increasing service and traffic demands from their geographically distributed users. Many ASPs and ISPs, such as Facebook, Netflix, AT&T and others have adopted micro-service architecture to tackle this problem. Instead of building a single, monolithic application, the idea is to split the application into a set of smaller, interconnected services, called micro-services (or simply services). Such services are lightweight and perform distinct tasks independent of each other. Hence, they can be deployed quickly and independently as user demands vary. Nevertheless, scheduling of micro-services is a complex task and is currently under-researched. In this work, we address the problem of scheduling micro-services across multiple clouds, including micro-clouds. We consider different user-level SLAs, such as latency and cost, while scheduling such services. Our aim is to reduce overall turnaround time for the complete end-to-end service in service function chains and reduce the total traffic generated. In this work we present a novel fair weighted affinity-based scheduling heuristic to solve this problem. We also compare the results of proposed solution with standard biased greedy scheduling algorithms presented in the literature and observe significant improvements.

Facilitating teachers in developing online PBL courses

Developing a sound online problem-based learning (PBL) course plan is difficult because teachers need comprehensive PBL and technical knowledge. This paper proposes a model-driven approach to develop a PBL authoring tool that helps teachers create and customize online PBL course plans in a cost-effective and flexible manner. A pilot study was conducted to assess teacher acceptance of the tool. The results reveal that after a short training session, teachers understood the authoring tool and thought the tool was easy to use to develop online PBL course plans.

COLAP: A predictive framework for service function chain placement in a multi-cloud environment

Network function virtualization (NFV) over multi-cloud promises network service providers amazing flexibility in service deployment and optimizing cost. Telecommunications applications are, however, sensitive to performance indicators, especially latency, which tend to get degraded by both the virtualization and the multiple cloud requirement for widely distributed coverage. In this work we propose an efficient framework that uses the novel concept of random cloud selection combined with a support vector regression based predictive model for cost optimized latency aware placement (COLAP) of service function chains. Extensive empirical analysis has been carried out with training datasets generated using a queuing-theoretic model. The results show good generalization performance of the predictive algorithm. The proposed framework can place thousands of virtual network functions in less than a minute and has high acceptance ratio.

Towards Pedagogy-Driven Learning Design: A Case Study of Problem-Based Learning Design

Existing learning design languages are pedagogy-neutral. They provide insufficient support to explicitly represent pedagogy-specific approaches such as problem-based learning (PBL). As the first step towards pedagogy-driven learning design, we developed a PBL design language and an associated authoring tool by adopting a domain-specific language (DSL) approach. The language and the tool provide means for teachers to think and represent their own PBL designs in vocabularies that the teacher daily uses to describe their PBL approaches. This paper presents a case study to investigate whether the language and the tool can facilitate the design of a PBL course plan. Although participants had minimal knowledge of PBL and were not skilled in process modeling, after a short training they were able to prepare their own PBL course plans using the PBL authoring tool. They reported that the vocabularies in the PBL design language were easy to understand. Some thought that the tool provides flexibility and others did not think so. Nevertheless, some found the process somewhat difficult to represent the narrative into a course plan. In addition, most participants found that the tool is user-friendly and easy to learn.