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Internet of things (IoT) is a network of smart things. This indicates the ability of these physical things to transfer information with other physical things. The characteristics of these networks, such as topology dynamicity and energy constraint, challenges the routing problem in these networks. Previous routing methods could not achieve the required performance in this type of network. Therefore, developers of this network designed and developed specific methods in order to satisfy the requirements of these networks. One of the routing methods is utilization of multipath protocols which send data to its destination using routes with separate links. One of such protocols is RPL routing protocol. In this paper, this method is improved using composite metrics which chooses the best paths used for separate routes to send packets. We propose Energy and Load aware RPL (ELaM-IoT) protocol, which is an enhancement of RPL protocol. It uses a composite metric, calculated based on remaining energy, hop count, Link Expiration Time (LET), load and battery depletion index (BDI) for the route selection. In order to evaluate and report the results, the proposed ELaM-IoT method is compared to the ERGID and ADRM-IoT approaches with regard to average remaining energy, and network lifetime. The results demonstrate the superior performance of the proposed ELaM-IoT compared to the ERGID and ADRM-IoT approaches.

This paper presents a novel approach for the design of microwave circuits using Adaptive Network Fuzzy Inference Optimizer (ANFIO). The method takes advantage of direct synthesis of subsections of the amplifier using very fast and accurate ANFIO models based on exact simulations using ADS. A mapping from course space to fine space known as space mapping is also used. The proposed synthesis approach takes into account the noise and scattering parameters due to parasitic elements to achieve optimal results. The overall ANFIO system is capable of designing different LNAs at different noise and scattering criteria. This approach offers significantly reduced time in the design of microwave amplifiers within the validity range of the ANFIO system. The method has been proven to work efficiently for a 2.4GHz LNA example. The S21 of 10.1 dB and noise figure (NF) of 2.7 dB achieved for ANFIO while S21 of 9.05 dB and NF of 2.6 dB achieved for ANN., {"references":["J.W. Bandler, Q.S. Cheng, N.K. Nikolova, and M.A. Ismail, \"Implicit\nspace mapping optimization exploiting preassigned parameters,\" IEEE\nTrans. Microwave Theory Tech., vol. 52, no. 1, pp. 378-385, Jan. 2004.","S. Koziel, J.W. Bandler, and K. Madsen, \"A space mapping framework\nFor engineering optimization: theory and implementation,\" IEEE Trans.\nMicrowave Theory Tech., vol. 54, no. 10, pp. 3721-3730, Oct. 2006.","A. Hennings, E. Semouchkina, A. Baker, and G. Semouchkin, \"Design\noptimization and implementation of bandpass filters with normally fed\nMicrostrip resonators loaded by high-permittivity dielectric,\" IEEE\nTrans.\nMicrowave Theory Tech., vol. 54, no. 3, pp. 1253-1261, March 2006.","J. W. Bandler, Q. S. Cheng, S. A. Dakroury, A. S. Mohamed, M. H.\nBakr, K. Madsen, J. Sondergaard , \"Space Mapping: The State of the\nArt,\" IEEE Trans. On Microwave Theory Tech., vol. 52, pp. 337-361,\n2004.","J.W. Bandler, Q.S. Cheng and S. Koziel, \"Simplified space mapping\napproach to enhancement of microwave device models,\" Int. J. RF and\nMicrowave Computer-Aided Eng., vol. 16, no. 5, pp. 518-535, 2006.","J. Zhu, J. W. Bandler, N. K. Nikolova and Koziel , \"Antenna\nOptimization Through Space Mapping,\" IEEE Trans. on Antennas and\nPropagation, vol. 55, pp. 651 - 658, 2007.","S. Koziel, J. W. Bandler, \"A Space-Mapping Approach to Microwave\nDevice Modeling Exploiting Fuzzy Systems,\" IEEE Trans. on\nMicrowave\nTheory and Tech.,vol. 55, pp. 2539 - 2547, 2007.","B. Karlik, H. Torpi, M. Alci, \"A fuzzy-neural approach for the\ncharacterization of the active microwave devices,\" 12th International\nConference on Microwave and Telecomm. Tech., pp. 114 - 117, 2002."]}