MWC 2016: AMD and Saguna Collaborate to Design Low-Power High-Performance Mobile Edge Computing (MEC) Solutions for Mobile Networks.
During #MWC16 Companies will demonstrate CloudFlare Content Acceleration MEC Application running on integrated platform.
AMD and Saguna collaborate to create scalable and economical Mobile Edge Computing (MEC) platforms for powering time-sensitive and bandwidth-intensive Internet of Things (IoT) and mobile data and video applications.
With the advent of IoT and the need to connect increasing numbers of connected devices, mobile networks face a tough scalability challenge. The need to secure the large volumes of data and content generated by these connected devices exacerbates the situation.
Addressing these challenges, AMD and Saguna are working to help mobile operators and system integrators transform the centric mobile network architecture with distributed edge computing operating inside the Radio Access Network (RAN), in close proximity to the end user or thing.
The pre-integrated platform design enables network vendors and system integrators to scale and secure mobile networks while creating a flexible MEC design that reduces time-to-market for developing and deploying new MEC services. The joint initiatives are based on Saguna Open-RAN MEC platform running on the high-performance AMD Embedded R-Series processor (codenamed "Merlin Falcon").
The AMD R-Series is a system-on-chip (SOC) that combines GPU and CPU processing resources that can simultaneously execute IPSec security, control, and data processing.
By packaging these capabilities in low-power processing architecture and bringing them to the edge of mobile networks, AMD processing can dramatically improve performance and increase security while helping reduce operating costs.
The Saguna Open-RAN MEC platform creates an open ecosystem and long-term growth engine inside the mobile RAN. The ETSI MEC standard-based solution enables mobile operators to quickly and effectively deploy new revenue generating services for content delivery, Internet-of-things (IoT) connectivity, retail and enterprise applications and more.
With fully virtualized software architecture, Saguna Open-RAN reduces CAPEX and OPEX promoting the adoption network function virtualization (NFV).
"As the number of mobile, connected devices continues to expand, AMD is thrilled to be working with Saguna to deliver secure, low-power platforms for Mobile Edge Computing," said Dilip Ramachandran, senior director of communications and networking, AMD Enterprise Solutions. "By working with Saguna, our customers can confidently scale the delivery of their services as their business and their customers' demands grow."
"We are very excited to collaborate with AMD to accelerate the growth of the MEC ecosystem. Our joint initiatives will expand community of mobile operators, system integrators and application developers, which can bring to market new MEC services and applications" said Ofer Talmor, Saguna's VP Products. "As MEC becomes a market standard, Saguna emerges as the most practical and advanced solution in the market today offering mobile operators the fastest track to a profitable high-performance network."
The companies will present their MEC solution running CloudFlare Mobile Edge application at the upcoming Mobile World Congress in Barcelona, Spain, scheduled for February 22-25, 2016.
The demonstrations will be held at AMD's meeting room Hall 2 Stand 2B52MR and Saguna's booth #5C81. To schedule a demo please clickhere.
Saguna Networks Saguna, a pioneer of Mobile Edge Computing (MEC), makes mobile broadband faster, simpler and more economical with smart NFV software solutions. Based on the ETSI MEC standard, the Saguna Open-RAN platform enables mobile operators to quickly and effectively deploy new revenue generating services. The Mobile Edge Computing platform has fully virtualized software architecture providing cost effective scalability and flexibility. For more information contact us at email@example.com, follow us @sagunanet or visit our website http://www.saguna.net.
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