Research

WAN Network data can be optimized at various levels depending upon the network applications, protocols, topology and use-cases. So the amount of data you can optimize will depend on the strategy you choose to optimize. Such as: Network Packet level optimization, Session level optimization, File level optimization, etc.

My 500GB Seagate Barracuda 7200RPM hard-drive suddenly started making mild clicking noise. I found this happening since morning. I was suspicious that something wrong in this drive and when I opened the Linux Disks app, I can find the cause of this issue. The disk is increasingly getting read errors. Besides I can see various other parameters such as Power-On Hours, Temperature, Head flying hours, etc.

PiPG is a powerful and yet simple Raspberry Pi Network Packet Generator. With PiPG you can now fabricate custom network packets and send via any Network Interface. Supports all kinds of standard Network Ports (Linux Kernel driver generated) such as Physical Network Interface ports, and an array of virtual ports such as loopback, tun/tap, bridge, etc. indispensable tool for: Network Debugging, Testing and Performance analysis Network Administrators Students Network R&D Protocol Analysis and Study Network Software Development Compliance Testing Ethical Hackers you can generate the following test traffic: L2-Bridging/Slow protocols: STP, LACP, OAM, LLDP, EAP, etc Routing protocols: RIPv1, RIPv2, IGMPv1, IGMPv2, OSPF, IS-IS, EIGRP, HSRP, VRRP, etc Proprietary protocols: CISCO, etc Generic: IPv4 TCP/UDP, etc Malformed random packets

If you want to deploy TOFFEE along with a web-proxy cache (such as Squid Proxy) you can deploy the same as shown below. TOFFEE does not cache files. TOFFEE does packet level network optimization. So if you want caching your web content you can use transparent mode web-proxy cache intercepting your WAN links. A web-proxy may reduce amount of data being processed (optimized) within these TOFFEE devices and so reduce the CPU overheads and improve its performance.

Today I completed doing all the changes which are meant for the new upcoming TOFFEE-Mocha release. I have increased the resolution and the range of all factor variables. Instead 1 to 10 range now they have a range of 1 to 30. Unlike before the value 1 means it is lot more intense (or in some cases less intense) and the uppermost value 30 means lot less intense (or in some cases lot intense).

I started TOFFEE-Mocha WAN Emulation software development on 1-June-2016. I took the existing TOFFEE components as a base. Although the TOFFEE-Mocha is entirely an independent fresh Open-Source WAN Emulation solution. Ever since I am in the process of defining and inventing features. So far I come up with the most important feature which is expected to be present in any WAN Emulation software is the packet delay option.

TOFFEE TOFFEE Data-Center is specifically meant for Data Center, Cluster Computing, HPC applications. TOFFEE is built in Linux Kernel core. This makes it inflexible to adapt according to the hardware configuration. It does sequential packet processing and does not scale up well in large multi-core CPU based systems (such as Intel Xeon servers, Core i7 Extreme Desktop systems,etc). Apart from this since it is kernel based, if there is an issue in kernel, it may crash entire system. This becomes a challenge for any carrier grade equipment (CGE) hardware build.

When you choose to use your Raspberry Pi device as your IoT based remote weather station or if you are building Linux kernel (like kernel compilation) within the same, you need a good uninterrupted power source (UPS). But if you are using it on site or in some research camping location you can choose to power your Raspberry Pi device with your custom off-grid solar power source.

Today I finally completed building my own private CDN. As I discussed so far in my earlier topics (Building my own CDN), I want to custom build the same step-by-step from scratch. And I don't want to for now use/buy third-party CDN subscriptions from Akamai, CloudFlare, Limelight, etc as I discussed earlier.

Here is my power-consumption measurements of various devices deployed within my home lab. I measured via my kill-a-watt sort of power-meter which is fairly reliable and accurate. I checked its accuracy with various standard load such as Philips LED laps and other constant power-consuming devices to make sure that the power-meter is precise.