Towards the Framing of Venture Capital Policies: a Systems-Evolutionary Perspective with Particular Reference to the UK/Scotland and Israeli Experiences

We compare some of the policies that have been attempted in Europe (UK/Scotland) and Israel over the past fifteen years to elaborate a new Systems Evolutionary (SE) framework for rethinking VC policy and related ITP. We argue that this perspective is useful for both real world (‘positive’) analysis and policy (‘normative’) analys is. Our SE framework is shaped by (i) a multidimensional view of VC; (ii) strong between VC, VC policy and the development of EHTCs; and (iii) a strategic approach to policy. In contrast, many VC policies in Europe up to and including the 1990s took a ‘static’ financial view of VC that focused on ‘bridging existng early phase finance gaps of innovative companies’ rather than creating of a new mechanism to assure the timely growth of EHTCs. We aim to present the new framework rather than to provide specific recommendations. The main conclusion is that the success of VC policies depend on factors such as the phase of evolution of (i) VC or related innovation finance organizations; (ii) the underlying segment of start up companies and of high tech industries; (iii) the specific country/region institutional setting. While in some contexts it may be worth considering the targeting of a new VC industry/market (and associated EHTC) in others the focus of policy should center in improving pre-emergence conditions. More specifically it may be, given that VC searches for ‘investment ready opportunities’, that ITP should, in many contexts, precede VC policies. Another key conclusion is that implementing this perspective necessitates the creation of a strategic level of policy, with a view of specifying a set of strategic priorities for Scie nce, Technology, and Innovation, priorities that should precede rather than follow policy design and implementation. A major challenge is to extend the present framework that was initially based on VCs oriented towards ICT to LS.

Autonomic Overload Management For Large-Scale Virtualized Network Functions

The explosion of data traffic in telecommunication networks has been impressive in the last few years. To keep up with the high demand and staying profitable, Telcos are embracing the Network Function Virtualization (NFV) paradigm by shifting from hardware network appliances to software virtual network functions, which are expected to support extremely large scale architectures, providing both high performance and high reliability. The main objective of this dissertation is to provide frameworks and techniques to enable proper overload detection and mitigation for the emerging virtualized software-based network services. The thesis contribution is threefold. First, it proposes a novel approach to quickly detect performance anomalies in complex and large-scale VNF services. Second, it presents NFV-Throttle, an autonomic overload control framework to protect NFV services from overload within a short period of time, allowing to preserve the QoS of traffic flows admitted by network services in response to both traffic spikes (up to 10x the available capacity) and capacity reduction due to infrastructure problems (such as CPU contention). Third, it proposes DRACO, to manage overload problems arising in novel large-scale multi-tier applications, such as complex stateful network functions in which the state is spread across modern key-value stores to achieve both scalability and performance. DRACO performs a fine-grained admission control, by tuning the amount and type of traffic according to datastore node dependencies among the tiers (which are dynamically discovered at run-time), and to the current capacity of individual nodes, in order to mitigate overloads and preventing hot-spots. This thesis presents the implementation details and an extensive experimental evaluation for all the above overload management solutions, by means of a virtualized IP Multimedia Subsystem (IMS), which provides modern multimedia services for Telco operators, such as Videoconferencing and VoLTE, and which is one of the top use-cases of the NFV technology

Dependability Evaluation of Middleware Technology for Large-scale Distributed Caching

Distributed caching systems (e.g., Memcached) are widely used by service providers to satisfy accesses by millions of concurrent clients. Given their large-scale, modern distributed systems rely on a middleware layer to manage caching nodes, to make applications easier to develop, and to apply load balancing and replication strategies. In this work, we performed a dependability evaluation of three popular middleware platforms, namely Twemproxy by Twitter, Mcrouter by Facebook, and Dynomite by Netflix, to assess availability and performance under faults, including failures of Memcached nodes and congestion due to unbalanced workloads and network link bandwidth bottlenecks. We point out the different availability and performance trade-offs achieved by the three platforms, and scenarios in which few faulty components cause cascading failures of the whole distributed system.Comment: 2020 IEEE 31st International Symposium on Software Reliability Engineering (ISSRE 2020