Presentation s contents

Transcription

1

2 Presentation s contents Vision statement Goal and objective Industry trends and pains Our value added proposition Recent news Next steps Incelligent s founding team and background Contact information

3 Our vision Bringing new generation wireless / mobile broadband networks to their full potential; Achieve environmental and economic sustainability, ease of management and optimal user experience.

4 Our direct goal To automate wireless network management enabling intelligent, real time decisions powered by accumulated knowledge

5 Industry trends and pains Data traffic explosion Cost increase Revenue slowly increasing Available options for cost efficiency almost exhausted Smart phones dominate 12X mobile traffic growth ( ) Video is the fastest growing application Mobile data traffic sources: Ericsson, June 2013

6 Industry trends and pains (cont.) Complex network Many cell technologies and sizes Macro, micro, pico, femto Many bands Individual-licensed (expensive) Light-licensed (less expensive) License-exempt (e.g., Wi-Fi) Many operators Shared networks More complex - Cells - Bands - Operators In a city: 100,000 small cells Serve: Millions of users Billions of Things How can all these cells/ resources be managed?

7 Our value added proposition Learning contexts (traffic, mobility, radio conditions in time and space, network state, running functions) Associating contexts with corresponding good solutions; Context: area, time, traffic levels When a known contextual situation is identified, a corresponding good solution is applied Solution: cells, spectrum per cell; potential for federating with operators Computationally intensive optimizations are conducted in the background, in order to fine-tune the knowledge on good solutions for traffic handling Complementary capabilities: governance, context predictions CONTEXT INFORMATION Traffic Mobility Radio conditions Interference Learning solutions per context Context Acquisition Incelligent software suite Optimization Interfaces Reasoning (Good solutions known?) Enforcement DECISION ENFORCEMENT Cells, spectrum that will be used for optimal and feasible context handling Additional capability Robustness and speed Limiting complexity

8 Expected benefits Human resources savings: Network procedures are automated Human involvement is limited Complex tradeoffs Opportunities for: Dynamic management of heterogeneous small cell deployment Cost & energy savings: Adaptation of network elements to traffic levels (e.g., low, medium, high, very high); when traffic is high more small cells can be activated; when traffic drops, small cells can be deactivated in order to save energy Spectrum aspects: Determination of appropriate spectrum bands in terms of cost Optimality with respect to energy consumption, QoE/QoS, minimization of human intervention Achieving speed and robustness of decisions Anticipated benefits at the order of 35-60% based on our studies and the literature

9 Openfund VC funds Incelligent

10 Achievements so far Alpha version of software already available Applied in realistic high demand use cases with promising results Released 1 st whitepaper analyzing the technology and some measurements on realistic use cases Engaged in discussions with top network equipment vendors for collaboration

11 Main focus areas High density wireless broadband networks WiFi networks (Public / Private) Licensed and unlicensed LTE networks Network sharing Machine to Machine / Internet of things

12 Impact at an indicative use case Network configuration A 1 km 2 large metropolitan metro station at the center of a big city The added value of Incelligent 18% less power Connecting 3 key transportation lines An average of 1000 LTE users move within from one platform to others 3-sector LTE macro BS, 3 Pico-cell hot spots (9 picos / hostspot) 20% more capacity 68% better customer experience 100% Incelligent network

13 Current work and next steps Measure Incelligent s beneficial impacts in additional challenging use cases Integrate Incelligent with widely adopted network vendors products Run pilots projects with selected wireless broadband network operators Release Beta Version

14 Founders Dr. Kostas Tsagkaris, Electrical & Computer Engineer, Technical Director & General Manager Experienced in the design, management and performance evaluation of autonomic/cognitive networks, self-organizing networks, software defined networks, optimization algorithms, learning techniques and software engineering. Strong in technical management of international and national projects related to management ICT for networks. Prof. Panagiotis Demestichas, Electrical & Computer Engineer, VP Research Professor at University of Piraeus, top scientist in telecommunication network design and management, queue management. Long experience in international and national research and development projects. Leading research on 5th generation wireless / mobile networks and mechanisms for management and design of wireless / mobile broadband networks. Dr. Serafim Kotrotsos, Electrical & Computer Engineer, VP Business Development Experienced in business development, productization, technical and business management. Having a long entrepreneurial background with significant achievements including the development and commercialization of innovative software products for the telecom industry. Strong in business consultancy, management and business strategy.

15 Founding company: WINGS ICT Solutions WINGS is a dynamic SME conducting research and developing solutions in ICT WINGS Strategy is built around: Smart Wireless Access Device Management Internet of Things (IoT) Big Data End-2-End Infrastructures

16 Contact information Syggrou A. Avenue, 336, Kallithea, Athens, Hellas