Capital equipment costs and energy costs are the major cost drivers in datacenters. Prior works have explored various techniques, like efficient scheduling algorithms and advanced power management techniques, to maximize resource utilization to reduce the capital and energy costs. The project HEXO has explored heterogeneous-Instruction Set Architecture (ISA) server-embedded clusters to minimize the cost. HEXO's key idea is to migrate stateful virtual machines from high-performance x86-based servers to low-power, low-cost ARM-based embedded boards, reducing server's resource congestion and thereby improving throughput and energy efficiency. However, embedded boards generally have significantly lower onboard memory, typically in the range of 100MB to 4GB. Due to this limitation, high memory-demand applications cannot be migrated to embedded devices. This limits the scope of applications that can be used with heterogeneous-ISA server-embedded clusters such as HEXO. This thesis proposes Netswap, a mechanism that utilizes the server's free memory as remote memory for the embedded board. Netswap comprises three main components: the swap-out and swap-in mechanism, a bitmap-based Free Memory Manager, and the Netswap Remote Daemon. Experimental studies using micro- and macro benchmarks reveal that Netswap improves the throughput and energy efficiency of server-embedded clusters by as much as 40% and 20%, respectively, over server-only baselines. / Master of Science / Datacenters have major expenditures like capital costs and energy expenditures. The project HEXO addresses in reducing these expenditures by including small embedded devices in datacenters. These embedded devices are cheaper and consume less energy than a typical server, but they have limited onboard RAM. The memory limitation restricts HEXO's ability to run applications with higher memory demand. This thesis introduces Netswap, which solves this issue by utilizing the free memory available on the servers as a secondary memory for the connected embedded devices. We discussed various design choices for efficiently implementing such a remote memory mechanism.