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来源:LM317 Electronics Components编辑:KYOCERA Corporation时间:2021-06-15 13:59:28

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Network virtualization technologies have evolved rapidly over the last few years, illustrating dramatic potential for evolution in longstanding network infrastructures. Combine this evolving technology with the growth of cloud computing, and the result is a surprisingly creative approach to improving data center performance and agility. Even enterprise networks firmly rooted in operational efficiencies are taking a fresh look at their data centers as a source for growth, competitive advantage and return on IT investment.

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The potential for transformation starts with the basic historical structure of a network–with physical servers once tiered for north-south data flow from access, distribution, and core layers to the wide area network and back again.Today that network is moving more and more traffic patterns that are east-west in nature, inherent to modern distributed systems and applications with data that moves across racks and pods.The result is swift adoption of fast, fat, and flat network topologies and network virtualization–creating deployments that rely on sophisticated switching technologies to deliver maximum scale and performance.

Initiating Network Transformation with VM-Aware Switching

Network usage models are indeed shifting rapidly, and network infrastructure designers must pay close attention to switching and virtualization requirements as part of this market's evolution.Global data traffic is increasing exponentially, anticipated to reach 26 times today’s level within the next three years, and millions of minutes of video are expected to cross the network every second. Connected devices are at the heart of this growth, and projections place the number of devices expanding to two times the global population by 2015. The highly scalable, virtualized network deployments that manage these transactions must rely on sophisticated switching technologies, enabling the full potential of applications that are sensitive to network performance.

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VM (virtual machine)-aware switching is essential in these environments, which increasingly require native OS-based server level performance, without performance penalties incurred by virtualized servers running multiple VMs.Several standards-based switching technologies such as SR-IOV (Single Root I/O Virtualization by PCI Special Interest Group) and VEPA/EVB (Virtual Ethernet Port Aggregator/Edge Virtual Bridging by IEEE 802.1) have emerged to address this consideration, and ensure improved performance and scalability of applications that run in VMs.

Effective VM switching means access layer switches in the data center network (e.g., top–of-rack switches, blade switches, or end-of-row switches) must support a large number of virtual switch ports (VSPs). In turn, VSPs in access layer switches must also support features including link aggregation, load balancing, traffic mirroring, and statistics counters similar to what is available for physical switch ports. Such features are essential to enabling VMs with the same level of reliability, performance, and monitoring as physical servers.

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VM-aware switches are engineered specifically to meet current feature and scale requirements of private and public cloud networks, a new essential in virtualized networks.Deployments can now feature virtual switch ports supporting high-level functionality, such as link aggregation, queuing, access control list (ACL), statistics, and mirroring services, that embodies many of the same services readily available in physical ports.

Smarter and More Flexible Deployments Lead the Market

Unfortunately, the power output of micro energy harvesters (Eh) is generally limited to some tens or hundreds of microwatts and the power consumption of RF-emitters or microcontrollers can reach some tens of milliwatts, banning a continuous running mode and implying intermittent measuring and data sending. Therefore, in EH and autonomous WSN, it is more appropriate to look at energy consumption for one measure instead of power consumption.

Also, it should be noted that the value 500µJ is a key number for WSN. This value corresponds to the needed energy to get a piece of information from the environment (temperature, humidity, etc.), to convert it into numeric data with an analog-to-digital converter (ADC) and to send it using standard protocols such as Bluetooth Low Energy or Zigbee. This energy could be reduced to some tens of µJ in the near future.

Therefore, functioning mode of EH-powered WSN can be summed up as follows (Figure 2 ): the energy harvesting device harvests power from its environment and stores it in a buffer (capacitor, battery) (1); µC, sensor and emitter are in standby and consume about 5µW. Measurement (2) and emission (3) are performed when enough energy is stored in the buffer. Buffer is emptied; system returns to standby, waiting for a new measurement cycle (4).

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